Slashdot Mirror
Text-Mining Your E-mail
Misha writes "There have been a number of weeks/months in anyone's life that called for a better organization of your Inbox. filtering and folders work, but it'd be nice to have an text-mining tool running in the background that categorized incoming messages by topic as they arrive. It's nice to see that besides NLP research, there are some great algorithmic advances being done, as seen in this paper. Perhaps even one of them Perl monkeys will quickly hack such a background tool." Note: it's a PostScript file.
Quarry Dirt Bird Earth Katz is a child m0lester Sand Raptor Earth Bird Earth Flyer Foul
Earth Worm Bird Katz is a child m0lester Worm Bird Earth Worm Foul Quarry Crust Foul
Katz is a child m0lester Raptor Quarry Earth Earth Dirt Sand Raptor Raptor Foul Foul Bird
Feathers Dirt Feathers Katz is a child m0lester Raptor Katz is a child m0lester Sand Katz is a child m0lester Earth Sand Sand Earth
Foul Flyer Worm Flyer Raptor Crust Katz is a child m0lester Sand Quarry Dirt Feathers Sand
Worm Quarry Flyer Bird Foul Katz is a child m0lester Flyer Katz is a child m0lester Raptor Flyer Sand Dirt
Bird Katz is a child m0lester Dirt Quarry Dirt Crust Sand Feathers Katz is a child m0lester Katz is a child m0lester Raptor Flyer
Earth Earth Worm Katz is a child m0lester Crust Foul Katz is a child m0lester Crust Dirt Katz is a child m0lester Feathers Foul
Sand Quarry Quarry Sand Katz is a child m0lester Sand Flyer Earth Quarry Feathers Foul Crust
Crust Crust Sand Crust Sand Flyer Flyer Feathers Foul Dirt Flyer Crust
Earth Bird Flyer Quarry Quarry Worm Quarry Quarry Dirt Raptor Flyer Worm
Sand Earth Bird Foul Bird Raptor Earth Raptor Foul Feathers Crust Raptor
Sand Crust Raptor Flyer Raptor Foul Katz is a child m0lester Bird Crust Sand Flyer Dirt
Raptor Bird Katz is a child m0lester Earth Foul Feathers Bird Crust Katz is a child m0lester Dirt Bird Worm
Quarry Dirt Worm Flyer Raptor Flyer Worm Bird Flyer Foul Flyer Foul
Raptor Foul Flyer Feathers Flyer Foul Katz is a child m0lester Earth Quarry Crust Earth Feathers
Quarry Bird Dirt Dirt Katz is a child m0lester Bird Katz is a child m0lester Earth Raptor Sand Dirt Earth
Dirt Feathers Katz is a child m0lester Earth Flyer Worm Flyer Flyer Earth Raptor Flyer Worm
Foul Raptor Katz is a child m0lester Flyer Crust Dirt Earth Bird Sand Raptor Flyer Foul
Katz is a child m0lester Earth Worm Dirt Worm Raptor Bird Bird Quarry Foul Katz is a child m0lester Katz is a child m0lester
Dirt Flyer Sand Worm Raptor Raptor Quarry Feathers Worm Worm Worm Katz is a child m0lester
Dirt Raptor Quarry Worm Katz is a child m0lester Quarry Bird Quarry Dirt Katz is a child m0lester Bird Quarry
Katz is a child m0lester Foul Worm Katz is a child m0lester Katz is a child m0lester Feathers Katz is a child m0lester Sand Sand Raptor Katz is a child m0lester Sand
Worm Quarry Worm Katz is a child m0lester Bird Flyer Crust Worm Quarry Feathers Earth Raptor
Worm Katz is a child m0lester Raptor Foul Katz is a child m0lester Crust Foul Foul Crust Crust Earth Katz is a child m0lester
Crust Quarry Earth Quarry Feathers Foul Bird Raptor Katz is a child m0lester Earth Flyer Flyer
Raptor Feathers Feathers Flyer Katz is a child m0lester Foul Flyer Foul Bird Feathers Feathers Bird
Flyer Raptor Katz is a child m0lester Worm Quarry Bird Raptor Bird Flyer Foul Earth Earth
Earth Crust Feathers Dirt Earth Katz is a child m0lester Flyer Earth Crust Feathers Katz is a child m0lester Feathers
Foul Crust Quarry Quarry Feathers Sand Earth Dirt Worm Bird Sand Raptor
Dirt Dirt Crust Feathers Crust Crust Quarry Foul Feathers Foul Raptor Foul
Flyer Crust Raptor Bird Sand Foul Crust Dirt Raptor Dirt Quarry Dirt
Earth Dirt Crust Flyer Flyer Worm Crust Bird Bird Feathers Foul Foul
Bird Dirt Earth Foul Worm Bird Foul Foul Foul Sand Dirt Quarry
Quarry Foul Earth Foul Earth Worm Quarry Feathers Katz is a child m0lester Flyer Quarry Feathers
Worm Worm Earth Feathers Flyer Sand Foul Dirt Flyer Bird Sand Earth
Quarry Foul Bird Katz is a child m0lester Foul Bird Sand Raptor Quarry Bird Flyer Foul
Bird Bird Raptor Foul Crust Dirt Bird Raptor Feathers Dirt Sand Bird
Katz is a child m0lester Crust Foul Katz is a child m0lester Flyer Foul Quarry Foul Sand Flyer Sand Crust
Dirt Flyer Bird Dirt Earth Flyer Earth Crust Katz is a child m0lester Worm Foul Katz is a child m0lester
Worm Foul Earth Foul Crust Earth Flyer Earth Earth Foul Bird Feathers
Sand Bird Feathers Katz is a child m0lester Dirt Crust Flyer Foul Foul Earth Bird Crust
Feathers Bird Sand Bird Raptor Feathers Dirt Feathers Crust Crust Worm Worm
Raptor Raptor Quarry Foul Earth Crust Bird Quarry Flyer Sand Sand Quarry
Quarry Bird Bird Worm Dirt Feathers Raptor Earth Earth Worm Raptor Dirt
Foul Foul Dirt Feathers Worm Flyer Earth Feathers Sand Raptor Quarry Dirt
Earth Katz is a child m0lester Dirt Flyer Foul Quarry Katz is a child m0lester Flyer Katz is a child m0lester Bird Crust Sand
Flyer Katz is a child m0lester Katz is a child m0lester Foul Dirt Flyer Dirt Flyer Foul Raptor Katz is a child m0lester Raptor
Raptor Foul Foul Raptor Sand Raptor Earth Dirt Earth Feathers Raptor Foul
Crust Raptor Raptor Earth Bird Flyer Worm Katz is a child m0lester Dirt Flyer Worm Foul
Crust Earth Quarry Sand Foul Bird Feathers Bird Raptor Worm Raptor Dirt
Foul Sand Sand Quarry Crust Worm Flyer Dirt Sand Bird Foul Dirt
Sand Flyer Quarry Worm Sand Bird Katz is a child m0lester Quarry Quarry Sand Foul Worm
Earth Feathers Bird Dirt Raptor Worm Feathers Bird Earth Bird Dirt Crust
Sand Earth Sand Worm Foul Sand Feathers Worm Foul Foul Crust Bird
Earth Bird Feathers Quarry Flyer Foul Bird Foul Quarry Earth Dirt Foul
Crust Flyer Worm Bird Bird Sand Earth Quarry Sand Foul Bird Flyer
Katz is a child m0lester Dirt Dirt Feathers Worm Raptor Dirt Sand Crust Quarry Crust Crust
Katz is a child m0lester Flyer Sand Katz is a child m0lester Earth Feathers Feathers Raptor Flyer Feathers Quarry Worm
Quarry Earth Crust Dirt Earth Flyer Katz is a child m0lester Crust Flyer Bird Raptor Dirt
Feathers Bird Dirt Bird Flyer Feathers Earth Raptor Raptor Feathers Earth Earth
Bird Katz is a child m0lester Katz is a child m0lester Worm Earth Feathers Flyer Worm Foul Dirt Katz is a child m0lester Flyer
Feathers Katz is a child m0lester Bird Raptor Foul Quarry Feathers Feathers Dirt Feathers Katz is a child m0lester Raptor
Bird Worm Katz is a child m0lester Dirt Dirt Crust Earth Sand Sand Worm Foul Crust
Sand Foul Raptor Feathers Foul Earth Crust Dirt Crust Flyer Crust Bird
Katz is a child m0lester Worm Katz is a child m0lester Raptor Crust Crust Dirt Earth Raptor Sand Crust Bird
Feathers Worm Dirt Quarry Quarry Earth Raptor Feathers Worm Raptor Earth Feathers
Sand Feathers Bird Quarry Flyer Katz is a child m0lester Foul Worm Dirt Sand Feathers Raptor
Crust Earth Raptor Flyer Quarry Quarry Quarry Feathers Sand Foul Dirt Feathers
Sand Dirt Crust Quarry Quarry Sand Sand Bird Raptor Feathers Bird Foul
Flyer Bird Worm Flyer Foul Katz is a child m0lester Earth Katz is a child m0lester Dirt Quarry Feathers Quarry
Katz is a child m0lester Foul Sand Foul Bird Sand Foul Earth Foul Earth Bird Foul
Foul Bird Crust Sand Flyer Flyer Crust Flyer Katz is a child m0lester Raptor Feathers Quarry
Earth Quarry Sand Earth Bird Sand Dirt Foul Worm Worm Quarry Sand
Foul Crust Quarry Raptor Sand Katz is a child m0lester Foul Katz is a child m0lester Worm Quarry Dirt Feathers
Worm Dirt Foul Worm Sand Feathers Foul Flyer Crust Earth Sand Sand
Bird Worm Crust Earth Sand Flyer Foul Worm Foul Feathers Katz is a child m0lester Flyer
Bird Feathers Flyer Quarry Bird Feathers Foul Dirt Feathers Sand Sand Flyer
Flyer Foul Earth Bird Katz is a child m0lester Quarry Earth Bird Quarry Katz is a child m0lester Flyer Flyer
Dirt Feathers Foul Sand Raptor Katz is a child m0lester Worm Crust Flyer Crust Worm Foul
Foul Katz is a child m0lester Crust Flyer Quarry Foul Raptor Feathers Katz is a child m0lester Dirt Worm Crust
Earth Raptor Foul Worm Dirt Sand Flyer Katz is a child m0lester Katz is a child m0lester Bird Dirt Katz is a child m0lester
Feathers Bird Raptor Bird Dirt Foul Quarry Dirt Quarry Katz is a child m0lester Raptor Raptor
Dirt Earth Feathers Katz is a child m0lester Crust Sand Feathers Earth Foul Dirt Raptor Dirt
Crust Bird Crust Dirt Sand Worm Quarry Crust Quarry Katz is a child m0lester Foul Feathers
Worm Earth Sand Katz is a child m0lester Dirt Flyer Katz is a child m0lester Bird Sand Foul Foul Quarry
Earth Worm Flyer Feathers Crust Feathers Raptor Flyer Flyer Earth Flyer Bird
Foul Quarry Raptor Quarry Flyer Sand Raptor Worm Crust Dirt Raptor Crust
Flyer Raptor Worm Foul Flyer Dirt Feathers Foul Foul Raptor Earth Foul
Katz is a child m0lester Dirt Earth Raptor Sand Flyer Katz is a child m0lester Crust Dirt Quarry Sand Earth
Sand Quarry Raptor Foul Quarry Flyer Foul Dirt Katz is a child m0lester Earth Flyer Foul
Raptor Flyer Foul Earth Quarry Earth Katz is a child m0lester Bird Bird Worm Worm Dirt
Quarry Crust Sand Crust Katz is a child m0lester Foul Raptor Raptor Bird Foul Quarry Crust
Feathers Feathers Dirt Crust Katz is a child m0lester Katz is a child m0lester Dirt Earth Crust Worm Earth Feathers
Feathers Katz is a child m0lester Raptor Feathers Foul Dirt Flyer Crust Dirt Sand Bird Worm
Crust Bird Sand Feathers Flyer Raptor Feathers Worm Dirt Earth Katz is a child m0lester Worm
Crust Foul Foul Sand Sand Raptor Foul Earth Flyer Flyer Dirt Earth
Katz is a child m0lester Foul Flyer Flyer Worm Dirt Katz is a child m0lester Feathers Dirt Crust Sand Sand
Crust Worm Foul Raptor Dirt Katz is a child m0lester Dirt Feathers Sand Foul Bird Worm
Flyer Foul Foul Worm Bird Quarry Foul Katz is a child m0lester Foul Earth Foul Earth
Katz is a child m0lester Katz is a child m0lester Worm Quarry Foul Katz is a child m0lester Worm Dirt Katz is a child m0lester Earth Worm Sand
Bird Katz is a child m0lester Flyer Worm Katz is a child m0lester Earth Earth Earth Raptor Feathers Flyer Feathers
Feathers Crust Earth Foul Katz is a child m0lester Foul Worm Worm Dirt Dirt Sand Worm
Foul Sand Flyer Worm Sand Flyer Sand Foul Feathers Earth Flyer Raptor
Flyer Katz is a child m0lester Crust Quarry Dirt Crust Flyer Earth Sand Raptor Feathers Bird
Earth Crust Dirt Crust Flyer Crust Raptor Sand Dirt Foul Dirt Worm
Crust Worm Dirt Dirt Worm Dirt Raptor Sand Dirt Flyer Foul Foul
Foul Worm Earth Foul Crust Quarry Crust Bird Sand Earth Sand Dirt
Crust Feathers Bird Bird Feathers Foul Earth Flyer Earth Bird Sand Foul
Crust Dirt Foul Feathers Raptor Katz is a child m0lester Crust Dirt Worm Quarry Foul Katz is a child m0lester
Sand Flyer Feathers Raptor Katz is a child m0lester Raptor Quarry Quarry Flyer Flyer Dirt Katz is a child m0lester
Worm Earth Foul Sand Katz is a child m0lester Crust Worm Earth Foul Quarry Raptor Flyer
Crust Feathers Feathers Bird Foul Katz is a child m0lester Crust Flyer Raptor Earth Quarry Bird
Raptor Sand Flyer Earth Feathers Bird Raptor Sand Foul Dirt Quarry Feathers
Bird Earth Earth Crust Raptor Bird Flyer Dirt Katz is a child m0lester Sand Flyer Foul
Crust Worm Katz is a child m0lester Raptor Sand Flyer Earth Dirt Feathers Raptor Sand Earth
Sand Feathers Bird Raptor Crust Dirt Bird Foul Dirt Bird Sand Feathers
Crust Flyer Feathers Feathers Earth Raptor Flyer Katz is a child m0lester Quarry Worm Worm Bird
Worm Katz is a child m0lester Bird Katz is a child m0lester Flyer Worm Earth Feathers Sand Feathers Sand Katz is a child m0lester
Crust Dirt Sand Feathers Dirt Bird Feathers Quarry Sand Feathers Bird Katz is a child m0lester
Katz is a child m0lester Earth Foul Feathers Foul Raptor Sand Foul Sand Bird Feathers Foul
Flyer Feathers Raptor Earth Quarry Raptor Foul Flyer Foul Dirt Crust Worm
Earth Flyer Raptor Worm Earth Feathers Foul Feathers Foul Sand Worm Katz is a child m0lester
Earth Worm Dirt Feathers Crust Bird Bird Worm Raptor Quarry Foul Flyer
Dirt Sand Raptor Raptor Earth Sand Earth Katz is a child m0lester Katz is a child m0lester Raptor Dirt Quarry
Dirt Quarry Katz is a child m0lester Worm Worm Katz is a child m0lester Katz is a child m0lester Foul Bird Earth Bird Flyer
Crust Dirt Feathers Crust Quarry Crust Dirt Raptor Feathers Feathers Feathers Earth
Earth Katz is a child m0lester Flyer Flyer Sand Feathers Dirt Worm Crust Worm Earth Feathers
Crust Crust Katz is a child m0lester Raptor Sand Crust Sand Katz is a child m0lester Foul Earth Earth Bird
Dirt Foul Raptor Foul Earth Foul Dirt Earth Dirt Bird Foul Crust
Bird Crust Quarry Sand Raptor Earth Dirt Bird Earth Quarry Feathers Flyer
Flyer Katz is a child m0lester Raptor Worm Flyer Dirt Sand Feathers Foul Flyer Raptor Feathers
Sand Foul Quarry Flyer Earth Worm Earth Raptor Foul Bird Sand Flyer
Sand Crust Raptor Foul Feathers Sand Sand Dirt Dirt Worm Katz is a child m0lester Raptor
Bird Foul Earth Dirt Quarry Earth Raptor Katz is a child m0lester Katz is a child m0lester Earth Dirt Worm
Raptor Foul Dirt Dirt Sand Dirt Katz is a child m0lester Foul Quarry Bird Worm Quarry
Katz is a child m0lester Dirt Earth Quarry Earth Feathers Earth Feathers Earth Dirt Sand Bird
Earth Flyer Dirt Feathers Bird Worm Earth Sand Dirt Raptor Feathers Foul
Dirt Raptor Earth Quarry Feathers Foul Foul Crust Earth Crust Bird Sand
Earth Foul Earth Feathers Sand Quarry Sand Worm Earth Dirt Katz is a child m0lester Raptor
Feathers Katz is a child m0lester Foul Feathers Flyer Bird Quarry Dirt Raptor Bird Bird Worm
Crust Raptor Katz is a child m0lester Sand Crust Sand Crust Quarry Raptor Crust Raptor Raptor
Bird Earth Dirt Crust Flyer Flyer Crust Foul Earth Sand Worm Quarry
Bird Flyer Sand Foul Sand Earth Quarry Raptor Flyer Katz is a child m0lester Dirt Sand
Quarry Dirt Dirt Katz is a child m0lester Sand Katz is a child m0lester Feathers Quarry Foul Katz is a child m0lester Crust Katz is a child m0lester
Raptor Earth Sand Quarry Bird Crust Crust Foul Foul Earth Feathers Feathers
Worm Sand Dirt Katz is a child m0lester Foul Crust Foul Raptor Feathers Worm Quarry Quarry
Feathers Feathers Katz is a child m0lester Earth Quarry Quarry Foul Bird Sand Sand Bird Feathers
Flyer Crust Worm Worm Raptor Bird Sand Foul Dirt Foul Katz is a child m0lester Dirt
Dirt
Slashdot, come for the goatse, stay for the trolls.
zeroth post!
Wow, that's terribly useful! Somebody convert it to PDF, mmmkay?
"next to first post"..
See? told you so.
They'll end up finding a loophole in your filtering, or you'll end up filtering out real emails.
Only way to win is to kill it from the source. End of story.
Here's to the researchers. I would like:
* An email box that lets me extract the threads with my friends.
* An email box that automatically ages the files effectively archiving them. Some of my mail folders/files are huge now and it takes too long to append them when new mail arrives.
Yes, I realize I should get off my butt and do this, but it's faster to post on slashdot.
Here's a link to a terribly useful site for converting your postscripts and word docs into pdf or jpeg.
I was thinking of how to intentionally fail my drug test... It would make a good memoir story someday.
Yes, soon someone will use such techniques to
generate a nice little background console app
to scan Slashdot to automatically fire out
First Posts and "Imagine a beowulf cluster of
these!" on the relevant topics. Truly the
best possible use of data mining. (:
Missle Missle Soldier Israel Soldier Death Massacre Raped Raped Death Assaulted Israel
Missle Abused Soldier Attacked Attacked Raped Child Missle Missle Assaulted Palastine Attacked
Palastine Israel Palastine Missle Death Massacre Palastine Attacked Missle Israel Assaulted Death
Missle Death Assaulted Assaulted Missle Child Abused Murdered Israel Palastine Israel Palastine
Palastine Attacked Raped Attacked Raped Palastine Assaulted Death Abused Death Raped Abused
Raped Murdered Missle Raped Israel Massacre Attacked Palastine Israel Attacked Palastine Palastine
Israel Raped Soldier Palastine Missle Abused Death Attacked Assaulted Assaulted Abused Raped
Murdered Raped Murdered Raped Murdered Raped Massacre Child Israel Murdered Abused Abused
Missle Massacre Palastine Massacre Massacre Raped Israel Raped Death Raped Palastine Abused
Attacked Soldier Attacked Assaulted Palastine Massacre Assaulted Israel Israel Murdered Raped Missle
Raped Assaulted Abused Abused Death Child Child Israel Child Raped Raped Attacked
Missle Missle Assaulted Child Death Assaulted Child Abused Assaulted Assaulted Attacked Child
Abused Child Abused Attacked Abused Massacre Massacre Abused Attacked Israel Missle Death
Raped Palastine Abused Death Soldier Attacked Soldier Assaulted Child Raped Soldier Missle
Raped Palastine Missle Palastine Palastine Raped Murdered Death Missle Attacked Soldier Palastine
Israel Soldier Murdered Death Child Attacked Child Soldier Death Attacked Missle Child
Israel Death Israel Death Assaulted Massacre Massacre Palastine Raped Soldier Death Assaulted
Death Attacked Soldier Assaulted Child Abused Soldier Soldier Massacre Soldier Soldier Murdered
Child Soldier Attacked Soldier Raped Abused Child Israel Assaulted Attacked Palastine Death
Massacre Israel Israel Palastine Massacre Abused Palastine Child Missle Massacre Murdered Israel
Murdered Assaulted Attacked Missle Soldier Assaulted Raped Child Murdered Child Massacre Raped
Massacre Child Murdered Attacked Murdered Assaulted Israel Israel Abused Assaulted Murdered Abused
Assaulted Murdered Massacre Murdered Raped Israel Murdered Missle Soldier Attacked Murdered Israel
Assaulted Murdered Child Child Missle Raped Assaulted Massacre Soldier Assaulted Assaulted Israel
Soldier Israel Murdered Massacre Death Murdered Attacked Missle Soldier Palastine Attacked Raped
Soldier Attacked Massacre Missle Raped Missle Assaulted Palastine Assaulted Missle Palastine Raped
Death Abused Palastine Raped Missle Palastine Abused Abused Soldier Israel Assaulted Palastine
Soldier Death Assaulted Murdered Attacked Raped Assaulted Palastine Child Soldier Raped Massacre
Murdered Missle Palastine Raped Abused Death Soldier Assaulted Israel Raped Attacked Abused
Abused Assaulted Massacre Israel Death Abused Death Attacked Assaulted Israel Assaulted Murdered
Missle Abused Child Missle Assaulted Israel Abused Soldier Soldier Israel Child Israel
Raped Raped Palastine Assaulted Soldier Child Raped Murdered Death Missle Raped Massacre
Missle Soldier Assaulted Murdered Death Murdered Death Massacre Soldier Missle Missle Child
Missle Attacked Israel Abused Missle Israel Raped Raped Palastine Massacre Murdered Palastine
Attacked Attacked Massacre Assaulted Attacked Missle Assaulted Assaulted Abused Palastine Palastine Soldier
Abused Child Murdered Massacre Raped Soldier Murdered Attacked Israel Abused Attacked Assaulted
Child Abused Israel Death Soldier Massacre Attacked Assaulted Assaulted Assaulted Soldier Child
Death Attacked Death Palastine Soldier Raped Soldier Raped Assaulted Massacre Palastine Attacked
Assaulted Murdered Abused Abused Soldier Raped Abused Raped Soldier Massacre Abused Child
Assaulted Murdered Assaulted Israel Massacre Massacre Attacked Assaulted Raped Murdered Massacre Raped
Death Palastine Murdered Soldier Israel Abused Death Missle Israel Child Massacre Assaulted
Israel Raped Attacked Death Assaulted Massacre Israel Assaulted Child Child Death Child
Palastine Murdered Soldier Missle Abused Child Palastine Massacre Child Missle Palastine Abused
Murdered Attacked Raped Raped Massacre Death Raped Soldier Attacked Israel Assaulted Abused
Missle Abused Raped Missle Child Abused Israel Soldier Missle Abused Palastine Soldier
Soldier Assaulted Missle Murdered Raped Palastine Death Israel Raped Child Soldier Massacre
Child Raped Child Missle Child Abused Massacre Attacked Massacre Attacked Massacre Murdered
Soldier Israel Massacre Missle Massacre Assaulted Israel Murdered Palastine Attacked Murdered Death
Assaulted Missle Death Assaulted Israel Child Death Abused Missle Raped Raped Attacked
Raped Massacre Massacre Missle Israel Massacre Attacked Attacked Soldier Attacked Child Abused
Murdered Abused Death Missle Massacre Assaulted Assaulted Soldier Abused Abused Massacre Death
Missle Massacre Attacked Missle Attacked Massacre Raped Death Raped Soldier Murdered Palastine
Soldier Assaulted Attacked Murdered Attacked Attacked Soldier Massacre Death Death Assaulted Soldier
Death Murdered Attacked Child Abused Raped Palastine Assaulted Assaulted Massacre Murdered Murdered
Attacked Israel Missle Soldier Israel Soldier Raped Death Death Raped Massacre Raped
Attacked Missle Murdered Abused Death Israel Murdered Death Palastine Murdered Raped Murdered
Death Attacked Assaulted Death Assaulted Soldier Child Israel Death Child Death Death
Israel Attacked Assaulted Missle Raped Missle Abused Soldier Abused Attacked Death Murdered
Death Soldier Murdered Palastine Death Palastine Soldier Attacked Massacre Child Abused Soldier
Abused Soldier Raped Attacked Israel Assaulted Abused Soldier Raped Death Child Soldier
Assaulted Soldier Assaulted Attacked Child Assaulted Massacre Assaulted Massacre Death Soldier Raped
Child Massacre Missle Missle Soldier Israel Murdered Missle Murdered Murdered Soldier Raped
Abused Assaulted Child Attacked Soldier Murdered Missle Assaulted Abused Israel Assaulted Israel
Abused Soldier Soldier Abused Raped Attacked Attacked Death Raped Attacked Assaulted Soldier
Murdered Palastine Massacre Abused Child Missle Assaulted Israel Death Soldier Death Death
Soldier Death Death Israel Abused Abused Massacre Murdered Assaulted Raped Palastine Palastine
Missle Israel Murdered Raped Assaulted Massacre Death Missle Murdered Israel Abused Attacked
Palastine Palastine Massacre Assaulted Abused Murdered Assaulted Attacked Soldier Assaulted Palastine Israel
Death Death Child Attacked Missle Attacked Soldier Murdered Massacre Child Abused Israel
Murdered Raped Attacked Missle Raped Abused Assaulted Assaulted Raped Raped Death Abused
Abused Raped Massacre Child Soldier Israel Attacked Death Murdered Israel Palastine Attacked
Attacked Assaulted Assaulted Massacre Soldier Murdered Assaulted Massacre Israel Attacked Palastine Abused
Child Murdered Missle Murdered Raped Attacked Israel Child Soldier Attacked Palastine Death
Raped Palastine Death Assaulted Death Assaulted Death Murdered Soldier Abused Death Soldier
Murdered Assaulted Missle Raped Missle Raped Massacre Abused Missle Assaulted Assaulted Massacre
Palastine Israel Missle Murdered Israel Child Attacked Murdered Missle Death Israel Assaulted
Missle Raped Child Attacked Palastine Raped Abused Raped Palastine Attacked Israel Israel
Palastine Israel Israel Israel Missle Missle Attacked Raped Assaulted Israel Missle Murdered
Massacre Child Death Death Soldier Missle Assaulted Assaulted Abused Palastine Missle Missle
Murdered Palastine Soldier Assaulted Death Murdered Massacre Massacre Israel Child Soldier Abused
Assaulted Missle Assaulted Palastine Death Abused Raped Palastine Assaulted Raped Attacked Assaulted
Death Death Abused Massacre Death Israel Murdered Child Massacre Murdered Soldier Soldier
Israel Death Assaulted Death Murdered Abused Attacked Abused Missle Death Attacked Assaulted
Assaulted Child Missle Death Raped Missle Soldier Attacked Israel Child Abused Israel
Palastine Palastine Attacked Assaulted Death Soldier Murdered Missle Raped Massacre Missle Murdered
Child Palastine Murdered Israel Abused Child Missle Murdered Murdered Israel Soldier Soldier
Palastine Child Palastine Death Death Death Raped Missle Massacre Soldier Raped Attacked
Abused Israel Missle Child Massacre Palastine Death Attacked Attacked Death Massacre Raped
Death Attacked Soldier Child Raped Missle Death Attacked Death Death Attacked Attacked
Missle Death Murdered Death Death Assaulted Israel Raped Missle Missle Palastine Assaulted
Attacked Assaulted Death Missle Child Attacked Assaulted Abused Assaulted Israel Death Palastine
Missle Assaulted Child Murdered Palastine Murdered Israel Massacre Assaulted Missle Raped Massacre
Attacked Massacre Child Massacre Raped Missle Palastine Soldier Raped Missle Palastine Palastine
Abused Child Abused Abused Death Missle Assaulted Abused Abused Death Israel Soldier
Missle Raped Israel Abused Massacre Murdered Child Murdered Soldier Attacked Missle Israel
Abused Death Palastine Raped Israel Abused Child Attacked Israel Israel Israel Death
Massacre Death Murdered Attacked Massacre Palastine Palastine Israel Missle Missle Missle Soldier
Soldier Raped Abused Soldier Palastine Soldier Soldier Abused Raped Murdered Israel Massacre
Attacked Assaulted Raped Child Massacre Death Death Child Assaulted Death Palastine Attacked
Assaulted Raped Assaulted Raped Attacked Death Child Abused Palastine Soldier Massacre Raped
Assaulted Assaulted Murdered Soldier Abused Attacked Abused Palastine Palastine Assaulted Raped Missle
Palastine Israel Missle Abused Massacre Death Murdered Child Assaulted Attacked Attacked Raped
Murdered Attacked Death Raped Assaulted Israel Palastine Death Attacked Murdered Child Child
Death Abused Assaulted Raped Missle Murdered Missle Soldier Abused Raped Raped Raped
Palastine Attacked Death Attacked Missle Palastine Child Raped Death Massacre Massacre Missle
Abused Massacre Child Attacked Abused Assaulted Israel Soldier Child Palastine Murdered Massacre
Soldier Raped Raped Child Death Israel Palastine Israel Raped Missle Attacked Attacked
Raped Raped Soldier Raped Assaulted Soldier Murdered Abused Child Attacked Child Murdered
Massacre Attacked Missle Soldier Assaulted Attacked Assaulted Soldier Raped Death Assaulted Murdered
Abused Missle Child Massacre Assaulted Death Murdered Attacked Child Abused Murdered Missle
Child Abused Murdered Missle Raped Massacre Attacked Israel Soldier Assaulted Raped Abused
Israel Palastine Child Raped Child Palastine Murdered Child Missle Israel Israel Death
Palastine Israel Soldier Israel Massacre Child Child Israel Death Abused Murdered Murdered
Death Attacked Massacre Soldier Raped Child Child Soldier Child Death Raped Attacked
Murdered Death Murdered Palastine Massacre Missle Massacre Child Murdered Assaulted Soldier Attacked
Massacre Palastine Israel Death Soldier Abused Soldier Soldier Child Soldier Murdered Missle
Abused Child Raped Death Attacked Death Child Attacked Death Palastine Israel Israel
Massacre Palastine Abused Massacre Attacked Israel Murdered Abused Missle Massacre Attacked Attacked
Attacked Murdered Abused Raped Missle Attacked Palastine Missle Palastine Death Murdered Death
Murdered Palastine Abused Raped Israel Raped Massacre Abused Murdered Child Raped Massacre
Massacre Abused Israel Assaulted Raped Palastine Assaulted Death Soldier Attacked Abused Soldier
Death Israel Murdered Abused Death Death Attacked Raped Death Assaulted Soldier Murdered
Palastine Murdered Attacked Palastine Assaulted Attacked Soldier Missle Palastine Massacre Death Abused
Massacre Massacre Massacre Death Missle Death Raped Abused Attacked Israel Massacre Abused
Murdered Attacked Child Death Soldier Murdered Raped Child Massacre Massacre Attacked Death
Child Murdered Attacked Missle Soldier Attacked Abused Massacre Massacre Missle Attacked Abused
Abused Attacked Raped Assaulted Abused Raped Attacked Israel Soldier Missle Assaulted Israel
Assaulted Palastine Massacre Raped Attacked Assaulted Child Death Assaulted Attacked Murdered Soldier
Death Abused Massacre Abused Death Child Child Abused Soldier Raped Massacre Soldier
Assaulted Massacre Death Abused Attacked Abused Child Soldier Palastine Raped Assaulted Murdered
Palastine Raped Attacked Murdered Attacked Israel Child Palastine Abused Massacre Raped Attacked
Israel Soldier Palastine Attacked Missle Murdered Death Assaulted Raped Assaulted Soldier Abused
Raped Palastine Soldier Child Attacked Assaulted Palastine Assaulted Palastine Death Attacked Abused
Soldier Israel Raped Child Assaulted Abused Attacked Soldier Death Child Israel Israel
Child Soldier Missle Attacked Attacked Abused Attacked Assaulted Murdered Attacked Soldier Palastine
Attacked Soldier Missle Death Abused Murdered Abused Israel Raped Attacked Child Massacre
Soldier Israel Death Death Child Massacre Abused Attacked Abused Soldier Abused Abused
Palastine Assaulted Assaulted Israel Abused Soldier Massacre Soldier Abused Palastine Raped Israel
Assaulted Murdered Murdered Assaulted Missle Murdered Raped Palastine Massacre Massacre Palastine Child
Soldier Palastine Soldier Murdered Assaulted Raped Palastine Attacked Missle Missle Abused Murdered
Raped Abused Murdered Abused Massacre Missle Missle Child Death Soldier Raped Palastine
Abused Death Child Palastine Assaulted Assaulted Murdered Attacked Palastine Murdered Raped Soldier
Raped Attacked Child Abused Child Missle Assaulted Attacked Attacked Israel Massacre Child
Massacre Attacked Palastine Murdered Missle Death Israel Palastine Israel Soldier Palastine Murdered
Assaulted Attacked Abused Missle Attacked Abused Attacked Missle Death Massacre Palastine Attacked
Child Palastine Child Palastine Israel Assaulted Raped Soldier Massacre Abused Israel Massacre
Child Death Massacre Missle Missle Missle Soldier Massacre Israel Raped Death Massacre
Palastine Soldier Palastine Raped Assaulted Child Palastine Attacked Abused Death Assaulted Soldier
Murdered Attacked Murdered Assaulted Massacre Attacked Abused Massacre Murdered Israel Soldier Massacre
Israel
I'm sure I'm not alone in saying that having a good history of well filtered incoming, and especially just about all of my Outgoing (Outbox) available for searching. My Outbox has been a lifesaver several times when someone claims that they didn't have that (electronic) discussion with me. It's great to quote "in a message sent... ...I asked you to...".
That feature in the description is not text mining, just filtering.
-pyrrho
It automagically does full text indexing of all specified databases. To it, your Inbox is just another database.
"History doesn't repeat itself, but it does rhyme." Mark Twain
Soldier Assaulted Death Abused Israel Massacre Death Death Death Attacked Death Missle
Murdered Murdered Attacked Assaulted Missle Abused Murdered Palastine Child Raped Attacked Death
Israel Assaulted Death Missle Child Massacre Raped Murdered Raped Massacre Abused Massacre
Death Israel Assaulted Assaulted Murdered Assaulted Palastine Raped Abused Soldier Child Raped
Child Raped Attacked Massacre Massacre Palastine Raped Palastine Missle Raped Massacre Murdered
Murdered Murdered Murdered Child Death Massacre Death Israel Israel Soldier Missle Murdered
Israel Assaulted Child Massacre Attacked Palastine Israel Attacked Murdered Missle Attacked Palastine
Murdered Soldier Soldier Death Murdered Attacked Assaulted Massacre Child Palastine Massacre Abused
Missle Soldier Massacre Palastine Israel Palastine Raped Massacre Soldier Soldier Murdered Murdered
Raped Child Massacre Palastine Attacked Palastine Palastine Missle Massacre Death Assaulted Child
Murdered Murdered Attacked Death Murdered Attacked Missle Palastine Attacked Soldier Raped Attacked
Soldier Massacre Child Assaulted Abused Palastine Raped Raped Soldier Raped Murdered Abused
Soldier Attacked Soldier Soldier Assaulted Israel Attacked Palastine Abused Israel Missle Death
Palastine Missle Missle Missle Massacre Death Child Missle Missle Raped Murdered Abused
Palastine Death Murdered Raped Raped Assaulted Massacre Death Raped Soldier Assaulted Murdered
Soldier Assaulted Israel Soldier Raped Missle Raped Attacked Child Raped Abused Massacre
Assaulted Missle Child Child Palastine Palastine Soldier Raped Murdered Israel Soldier Attacked
Missle Massacre Death Missle Massacre Israel Child Raped Palastine Murdered Palastine Attacked
Palastine Massacre Israel Missle Murdered Massacre Attacked Soldier Death Attacked Assaulted Murdered
Child Israel Missle Raped Missle Murdered Assaulted Palastine Massacre Assaulted Abused Assaulted
Raped Assaulted Massacre Death Soldier Israel Soldier Child Israel Missle Murdered Soldier
Missle Assaulted Death Abused Murdered Abused Death Assaulted Massacre Assaulted Attacked Assaulted
Murdered Child Assaulted Missle Soldier Soldier Palastine Abused Death Assaulted Raped Child
Murdered Raped Death Israel Attacked Murdered Death Assaulted Assaulted Child Abused Death
Abused Israel Attacked Attacked Child Palastine Massacre Missle Palastine Missle Abused Murdered
Child Assaulted Massacre Child Raped Assaulted Missle Palastine Attacked Murdered Soldier Abused
Palastine Abused Massacre Death Raped Death Massacre Missle Attacked Raped Raped Attacked
Soldier Abused Raped Palastine Death Attacked Attacked Massacre Massacre Assaulted Assaulted Child
Assaulted Massacre Israel Israel Soldier Death Death Attacked Soldier Raped Murdered Abused
Abused Israel Missle Raped Missle Death Abused Murdered Murdered Abused Death Palastine
Abused Abused Death Murdered Death Missle Murdered Palastine Child Palastine Abused Murdered
Raped Abused Israel Attacked Assaulted Child Assaulted Massacre Palastine Child Attacked Child
Israel Attacked Murdered Israel Soldier Massacre Murdered Raped Assaulted Death Abused Israel
Soldier Soldier Child Palastine Abused Massacre Soldier Death Missle Israel Child Palastine
Child Soldier Soldier Abused Death Murdered Palastine Palastine Assaulted Assaulted Palastine Missle
Massacre Raped Abused Palastine Missle Soldier Missle Massacre Soldier Murdered Massacre Palastine
Death Israel Raped Israel Abused Soldier Abused Missle Missle Israel Massacre Israel
Murdered Palastine Attacked Soldier Palastine Child Attacked Murdered Assaulted Palastine Israel Massacre
Massacre Attacked Murdered Assaulted Massacre Assaulted Massacre Missle Soldier Abused Massacre Soldier
Massacre Missle Abused Palastine Missle Attacked Massacre Missle Death Raped Death Soldier
Raped Massacre Soldier Palastine Israel Attacked Attacked Israel Missle Missle Israel Missle
Abused Soldier Abused Missle Soldier Soldier Palastine Abused Israel Assaulted Child Palastine
Soldier Death Palastine Abused Israel Soldier Child Massacre Attacked Raped Abused Murdered
Raped Assaulted Missle Attacked Missle Massacre Death Raped Massacre Abused Raped Israel
Raped Soldier Abused Israel Palastine Massacre Israel Israel Palastine Child Death Assaulted
Attacked Child Murdered Abused Death Massacre Soldier Massacre Raped Attacked Attacked Missle
Soldier Death Murdered Israel Abused Missle Massacre Abused Child Massacre Attacked Israel
Massacre Death Massacre Murdered Death Soldier Palastine Death Palastine Murdered Palastine Israel
Assaulted Abused Child Child Raped Child Palastine Child Assaulted Attacked Abused Abused
Death Abused Murdered Palastine Abused Massacre Soldier Raped Assaulted Assaulted Murdered Murdered
Attacked Murdered Death Israel Raped Massacre Death Israel Assaulted Missle Israel Soldier
Massacre Death Assaulted Israel Raped Child Abused Israel Massacre Soldier Murdered Attacked
Massacre Israel Israel Assaulted Murdered Israel Massacre Attacked Israel Soldier Abused Child
Abused Assaulted Death Assaulted Soldier Palastine Abused Murdered Missle Missle Child Israel
Attacked Massacre Attacked Massacre Soldier Attacked Attacked Missle Attacked Child Abused Missle
Soldier Child Soldier Attacked Palastine Missle Raped Abused Raped Abused Soldier Child
Death Assaulted Abused Abused Abused Attacked Israel Murdered Abused Israel Abused Israel
Soldier Death Murdered Massacre Palastine Palastine Israel Child Child Death Israel Massacre
Raped Raped Assaulted Abused Attacked Murdered Soldier Israel Attacked Missle Israel Abused
Soldier Soldier Soldier Missle Palastine Palastine Abused Abused Soldier Raped Soldier Murdered
Murdered Massacre Murdered Abused Assaulted Abused Raped Attacked Murdered Murdered Raped Soldier
Death Massacre Missle Soldier Palastine Abused Murdered Raped Attacked Soldier Child Massacre
Soldier Assaulted Child Raped Attacked Raped Child Massacre Raped Abused Raped Massacre
Child Soldier Missle Missle Attacked Abused Attacked Israel Child Soldier Assaulted Israel
Murdered Israel Israel Assaulted Abused Assaulted Massacre Missle Raped Assaulted Death Murdered
Missle Soldier Assaulted Israel Death Soldier Palastine Israel Attacked Attacked Attacked Palastine
Raped Soldier Assaulted Assaulted Child Murdered Israel Massacre Raped Palastine Soldier Raped
Child Murdered Assaulted Missle Death Soldier Palastine Soldier Death Palastine Assaulted Death
Death Attacked Attacked Massacre Abused Death Palastine Attacked Attacked Child Israel Missle
Attacked Soldier Attacked Assaulted Raped Raped Raped Soldier Massacre Israel Child Massacre
Death Israel Raped Child Massacre Massacre Missle Palastine Child Soldier Murdered Missle
Palastine Attacked Abused Massacre Attacked Massacre Soldier Raped Attacked Soldier Child Attacked
Abused Death Missle Assaulted Attacked Massacre Attacked Massacre Missle Israel Attacked Missle
Attacked Attacked Abused Death Raped Child Assaulted Massacre Murdered Attacked Attacked Palastine
Attacked Missle Murdered Assaulted Raped Massacre Death Abused Massacre Child Raped Attacked
Death Assaulted Death Assaulted Palastine Massacre Murdered Soldier Murdered Abused Abused Missle
Soldier Child Abused Death Soldier Assaulted Soldier Death Missle Death Attacked Child
Missle Massacre Murdered Assaulted Murdered Death Abused Israel Abused Abused Missle Missle
Israel Raped Abused Abused Soldier Missle Child Missle Raped Death Soldier Raped
Abused Child Soldier Abused Assaulted Soldier Missle Abused Assaulted Massacre Abused Israel
Abused Missle Attacked Soldier Assaulted Raped Murdered Massacre Israel Death Soldier Death
Abused Missle Death Raped Missle Attacked Child Missle Murdered Raped Death Israel
Child Murdered Attacked Palastine Death Assaulted Massacre Abused Murdered Soldier Soldier Attacked
Massacre Attacked Palastine Attacked Soldier Raped Abused Child Assaulted Abused Death Missle
Death Abused Child Israel Massacre Massacre Child Assaulted Attacked Israel Attacked Soldier
Child Missle Raped Assaulted Palastine Abused Massacre Child Abused Missle Israel Israel
Attacked Death Death Raped Murdered Missle Soldier Abused Soldier Missle Assaulted Palastine
Death Assaulted Israel Assaulted Missle Assaulted Assaulted Abused Massacre Massacre Attacked Israel
Palastine Abused Murdered Missle Raped Massacre Murdered Attacked Murdered Palastine Abused Massacre
Abused Palastine Soldier Raped Attacked Soldier Palastine Abused Death Israel Death Palastine
Death Soldier Abused Child Missle Murdered Murdered Child Massacre Assaulted Raped Death
Assaulted Raped Israel Abused Soldier Palastine Murdered Child Death Abused Abused Raped
Soldier Death Attacked Attacked Raped Assaulted Death Israel Assaulted Child Missle Raped
Child Child Murdered Raped Murdered Palastine Child Soldier Murdered Raped Death Soldier
Assaulted Raped Massacre Palastine Abused Israel Murdered Child Raped Raped Soldier Soldier
Soldier Soldier Massacre Palastine Abused Attacked Missle Soldier Soldier Murdered Murdered Raped
Assaulted Attacked Palastine Assaulted Assaulted Child Israel Missle Massacre Death Assaulted Palastine
Palastine Missle Massacre Palastine Soldier Murdered Massacre Child Raped Death Israel Child
Murdered Death Soldier Assaulted Attacked Abused Israel Attacked Raped Abused Attacked Missle
Child Soldier Raped Palastine Child Death Child Assaulted Israel Murdered Death Murdered
Death Child Child Raped Palastine Raped Murdered Missle Raped Assaulted Palastine Attacked
Israel Abused Israel Death Massacre Child Palastine Massacre Massacre Assaulted Abused Murdered
Palastine Murdered Soldier Soldier Child Attacked Israel Child Raped Massacre Attacked Palastine
Assaulted Abused Assaulted Missle Massacre Soldier Israel Soldier Israel Child Assaulted Massacre
Israel Child Soldier Soldier Death Soldier Soldier Soldier Raped Soldier Attacked Raped
Child Death Massacre Death Attacked Death Massacre Murdered Soldier Raped Child Palastine
Israel Abused Abused Child Child Murdered Assaulted Missle Murdered Assaulted Death Raped
Abused Abused Missle Massacre Abused Attacked Soldier Death Palastine Israel Israel Child
Murdered Murdered Missle Missle Murdered Abused Massacre Abused Child Assaulted Murdered Assaulted
Palastine Attacked Attacked Massacre Murdered Abused Palastine Assaulted Massacre Assaulted Soldier Palastine
Missle Palastine Raped Raped Raped Abused Missle Abused Abused Attacked Attacked Raped
Raped Assaulted Assaulted Attacked Israel Raped Child Murdered Assaulted Raped Child Child
Israel Abused Soldier Attacked Attacked Israel Palastine Child Missle Death Abused Abused
Assaulted Soldier Soldier Israel Attacked Soldier Israel Attacked Murdered Raped Massacre Child
Missle Abused Death Missle Attacked Raped Attacked Death Assaulted Massacre Massacre Missle
Abused Attacked Child Child Soldier Murdered Child Death Israel Palastine Attacked Child
Palastine Death Soldier Raped Massacre Soldier Attacked Soldier Missle Massacre Massacre Child
Massacre Palastine Soldier Assaulted Massacre Raped Raped Death Abused Massacre Murdered Soldier
Abused Assaulted Attacked Murdered Soldier Abused Israel Murdered Massacre Massacre Abused Death
Assaulted Israel Assaulted Palastine Abused Soldier Palastine Israel Child Assaulted Missle Soldier
Raped Missle Child Murdered Death Missle Attacked Death Massacre Child Palastine Attacked
Israel Massacre Soldier Assaulted Death Missle Missle Child Massacre Missle Death Assaulted
Abused Murdered Missle Assaulted Raped Raped Raped Child Assaulted Child Israel Murdered
Soldier Death Abused Palastine Assaulted Massacre Israel Attacked Abused Attacked Death Raped
Soldier Raped Raped Israel Missle Soldier Attacked Raped Soldier Soldier Palastine Death
Raped Palastine Child Death Raped Soldier Abused Israel Raped Child Israel Soldier
Assaulted Murdered Child Abused Missle Assaulted Attacked Raped Palastine Palastine Missle Raped
Palastine Assaulted Child Israel Assaulted Massacre Attacked Raped Soldier Massacre Raped Soldier
Death Missle Palastine Death Israel Israel Israel Massacre Massacre Soldier Child Attacked
Assaulted Assaulted Massacre Abused Massacre Raped Raped Child Missle Soldier Soldier Palastine
Child Death Soldier Attacked Death Abused Raped Child Assaulted Child Attacked Palastine
Death Raped Israel Death Massacre Child Attacked Missle Attacked Murdered Missle Palastine
Child Missle Child Missle Raped Assaulted Murdered Assaulted Missle Murdered Missle Attacked
Child Israel Palastine Attacked Raped Murdered Israel Raped Israel Massacre Missle Abused
Palastine Abused Israel Soldier Missle Palastine Child Death Massacre Israel Massacre Assaulted
Massacre Attacked Israel Raped Soldier Abused Assaulted Assaulted Israel Murdered Missle Palastine
Palastine Murdered Death Raped Abused Abused Assaulted Massacre Soldier Palastine Missle Murdered
Child Abused Murdered Palastine Israel Israel Raped Assaulted Murdered Soldier Missle Massacre
Assaulted Murdered Death Raped Raped Israel Abused Child Palastine Missle Child Palastine
Missle Israel Massacre Child Israel Child Assaulted Missle Abused Death Palastine Murdered
Death Abused Child Abused Missle Palastine Attacked Raped Attacked Assaulted Massacre Abused
Murdered Assaulted Israel Soldier Child Palastine Assaulted Abused Massacre Israel Attacked Massacre
Soldier Israel Attacked Murdered Murdered Attacked Raped Massacre Soldier Missle Raped Abused
Child Murdered Raped Abused Palastine Missle Abused Israel Murdered Assaulted Soldier Soldier
Raped Soldier Palastine Raped Missle Assaulted Death Assaulted Israel Child Assaulted Missle
Raped Attacked Child Missle Abused Assaulted Death Death Massacre Raped Child Israel
Child Assaulted Massacre Attacked Abused Attacked Israel Palastine Child Palastine Soldier Abused
Soldier Assaulted Abused Soldier Missle Palastine Assaulted Palastine Child Soldier Soldier Assaulted
Abused Attacked Attacked Palastine Child Assaulted Abused Missle Attacked Abused Abused Assaulted
Abused
fucking transluscent butt-plugs are all the rage among those ass-reaming afficiandos like hemos, cmdrtaco and cowboy "ride-him-hard" neal.
while still transluscent, slight, tasteful tints of puce and mauve are best sellers right now. easily licked clean for more ass-reaming fun, get your tbp today for the low introductory "fuck a faggot for jesus" sale price of $1.00. or, if you prefer, you can suck off the general manager and tounge-fuck his asshole and get one free!
How can I forget something? I've just learnt something that I want to forget (in the past hour), and I want to forget it completely. It's pretty damn important. Thanks.
This would be an awesome tool to block spam. If this program could look at the text of an email message and determine that it is a solicitation of some kind and then drop it into an email "pit" (you know, a folder mapped to /dev/null), that would make my life a LOT easier...
The Dopester
"Yes, I'm a Karma Whore, but I'm doing it to pay my way through school."
Outlook?
"that categorized incoming messages by topic as they arrive." - you can already sort messages into different folders depending on their topic by setting up rules.
Video Game cheats, hints a
Personally, I'd prefer that I simply get less email. The fact that we need NLP tools to pre-screen our email for us just shows how information-overloaded our society has become. What I really need is a tool at the sender's end that can pre-screen my email and tell the sender "Don't send this. He just doesn't care!"
I can sort reports from devices, co-workers, clients....each goes in its own folder....
Bursty and Hierarchical Structure in Streams * Jon Kleinberg # Abstract A fundamental problem in text data mining is to extract meaningful structure from document streams that arrive continuously over time. E-mail and news articles are two natural examples of such streams, each characterized by topics that appear, grow in intensity for a period of time, and then fade away. The published literature in a particular research field can be seen to exhibit similar phenomena over a much longer time scale. Underlying much of the text mining work in this area is the following intuitive premise -- that the appearance of a topic in a document stream is signaled by a "burst of activity," with certain features rising sharply in frequency as the topic emerges. The goal of the present work is to develop a formal approach for modeling such "bursts," in such a way that they can be robustly and efficiently identified, and can provide an organizational framework for analyzing the underlying content. The approach is based on modeling the stream using an infinite-state automaton, in which bursts appear naturally as state transitions; in some ways, it can be viewed as drawing an analogy with models from queueing theory for bursty network traffic. The resulting algorithms are highly efficient, and yield a nested representation of the set of bursts that imposes a hierarchical structure on the overall stream. Experiments with e-mail and research paper archives suggest that the resulting structures have a natural meaning in terms of the content that gave rise to them. *A version of this work appears as Cornell Computer Science Technical Report 02-1863 (March 2002). #Department of Computer Science, Cornell University, Ithaca NY 14853. Email: kleinber@cs.cornell.edu. Supported in part by a David and Lucile Packard Foundation Fellowship, an ONR Young Investigator Award, NSF ITR/IM Grant IIS-0081334, and NSF Faculty Early Career Development Award CCR-9701399. 1. 1 Introduction Documents can be naturally organized by topic, but in many settings we also experience their arrival over time. E-mail and news articles provide two clear examples of such document streams: in both cases, the strong temporal ordering of the content is necessary for making sense of it, as particular topics appear, grow in intensity, and then fade away again. Over a much longer time scale, the published literature in a particular research field can be meaningfully understood in this way as well, with particular research themes growing and diminishing in visibility across a period of years. Work in the areas of topic detection and tracking [2, 3, 5, 61, 62], text mining [36, 56, 57, 58], and visualization [26, 43, 60] has explored techniques for identifying topics in document streams comprised of news stories, using a combination of content analysis and time-series modeling. Underlying a number of these techniques is the following intuitive premise -- that the appearance of a topic in a document stream is signaled by a "burst of activity," with certain features rising sharply in frequency as the topic emerges. The goal of the present work is to develop a formal approach for modeling such "bursts," in such a way that they can be robustly and efficiently identified, and can provide an organizational framework for analyzing the underlying content. At one level, the approach presented here can be viewed as drawing an analogy with models from queueing theory for bursty network traffic (see e.g. [32]). In addition, however, the analysis of the underlying burst patterns reveals a latent hierarchical structure that often has a natural meaning in terms of the content of the stream. My initial aim in studying this issue was a very concrete one: I wanted a better organizing principle for the enormous archives of personal e-mail that I was accumulating. Abundant anecdotal evidence, as well as academic research [6, 42, 59], suggested that my own experience with "e-mail overload" corresponded to a near-universal phenomenon -- a consequence of both the rate at which e-mail arrives, and the demands of managing volumes of saved personal correspondence that can easily grow into tens and hundreds of megabytes of pure text content. And at a still larger scale, e-mail has become the raw material for legal proceedings [34] and historical investigation [8, 38, 44] -- with the National Archives, for example, agreeing to accept tens of millions of e-mail messages from the Clinton White House [45]. In sum, there are several settings where it is a crucial problem to find structures that can help in making sense of large volumes of e-mail. An active line of research has applied text indexing and classification to develop e-mail interfaces that organize incoming messages into folders on specific topics, sometimes recommending further actions on the part of a user [4, 9, 13, 29, 30, 39, 46, 47, 49, 50, 51, 53, 54] -- in effect, this framework seeks to automate a kind of filing system that many users implement manually. There has also been work on developing query interfaces to fully-indexed collections of e-mail [7]. My interest here is in exploring organizing structures based more explicitly on the role of time in e-mail and other document streams. Indeed, even the flow of a single focused topic 2. is modulated by the rate at which relevant messages or documents arrive, dividing naturally into more localized episodes that correspond to bursts of activity of the type suggested above. For example, my saved e-mail contains over a thousand messages relevant to the topic "grant proposals" -- announcements of new funding programs, planning of proposals, and correspondence with co-authors. While one could divide this collection into sub-topics based on message content -- certain people, programs, or funding agencies form the topics of some messages but not others -- an equally natural and substantially orthogonal organization for this topic would take into account the sequence of episodes reflected in the set of messages -- bursts that surround the planning and writing of certain proposals. Indeed, certain subtopics (e.g. "the process of gathering people together for our large NSF ITR proposal") may be much more easily characterized by a sudden confluence of message-sending over a particular period of time than by textual features of the messages themselves. One can easily argue that many of the large topics represented in a document stream are naturally punctuated by bursts in this way, with the flow of relevant items intensifying in certain key periods. A general technique for highlighting these bursts thus has the potential to expose a great deal of fine-grained structure. Before moving to a more technical overview of the methodology, let me suggest one further perspective on this issue, quite distant from computational concerns. If one were to view a particular folder of e-mail not simply as a document stream but also as something akin to a narrative that unfolds over time, then one immediately brings into play a body of work that deals explicitly with the bursty nature of time in narratives, and the way in which particular events are signaled by a compression of the time-sense. In an early concrete reference to this idea, E.M. Forster, lecturing on the structure of the novel in the 1920's, asserted that . . . there seems something else in life besides time, something which may conveniently be called "value," something which is measured not by minutes or hours but by intensity, so that when we look at our past it does not stretch back evenly but piles up into a few notable pinnacles, and when we look at the future it seems sometimes a wall, sometimes a cloud, sometimes a sun, but never a chronological chart [17]. This role of time in narratives is developed more explicitly in work of Genette [19, 20], Chatman [11], and others on anisochronies, the non-uniform relationships between the amount of time spanned by a story's events and the amount of time devoted to these events in the actual telling of the story. Modeling Bursty Streams. Suppose we were presented with a document stream -- for concreteness, consider a large folder of e-mail on a single broad topic. How should we go about identifying the main bursts of activity, and how do they help impose additional structure on the stream? The basic point emerging from the discussion above is that such 3. bursts correspond roughly to points at which the intensity of message arrivals increases sharply, perhaps from once every few weeks or days to once every few hours or minutes. But the rate of arrivals is in general very "rugged": it does not typically rise smoothly to a crescendo and then fall away, but rather exhibits frequent alternations of rapid flurries and longer pauses in close proximity. Thus, methods that analyze gaps between consecutive message arrivals in too simplistic a way can easily be pulled into identifying large numbers of short spurious bursts, as well as fragmenting long bursts into many smaller ones. Moreover, a simple enumeration of close-together sets of messages is only a first step toward more intricate structure. The broader goal is thus to extract global structure from a robust kind of data reduction -- identifying bursts only when they have sufficient intensity, and in a way that allows a burst to persist smoothly across a fairly non-uniform pattern of message arrivals. My approach here is to model the stream using an infinite-state automaton A, which at any point in time can be in one of an underlying set of states, and emits messages at different rates depending on its state. Specifically, the automaton A has a set of states that correspond to increasingly rapid rates of emission, and the onset of a burst is signaled by a state transition -- from a lower state to a higher state. By assigning costs to state transitions, one can control the frequency of such transitions, preventing very short bursts and making it easier to identify long bursts despite transient changes in the rate of the stream. The overall framework is developed in Section 2. It can be viewed as drawing an analogy to the use of on-off Markov sources in modeling bursty network traffic (see for example the overview article by Kelly [32]), as well as drawing on the formalism of hidden Markov models [48]. Using an automaton with states that correspond to higher and higher intensities provides an additional source of analytical leverage -- the bursts associated with state transitions form a naturally nested structure, with a long burst of low intensity potentially containing several bursts of higher intensity inside it (and so on, recursively). For a folder of related e-mail messages, we will see in Sections 2 and 3 that this can provide a hierarchical decomposition of the temporal order, with long-running episodes intensifying into briefer ones according to a natural tree structure. This tree can thus be viewed as imposing a fine-grained organization on the sub-episodes within the message stream. Following this development, Section 4 focuses on a case in which the document stream is comprised not of e-mail messages but of computer science conference paper titles over the past several decades; the set of bursts in this stream corresponds roughly to the appearance and disappearance of certain terms of interest in the papers. Section 5 discusses the connections to related work in a range of areas, particularly the striking recent work of Swan, Allan, and Jensen [56, 57, 58] on overview timelines, which forms the body of research closest to the approach here. Finally, Section 6 discusses some further applications of the methodology -- how burstiness in arrivals can help to identify certain messages as "landmarks" in a large corpus of e-mail; and how the overall framework can be applied to logs of Web traffic. 4. 2 A Weighted Automaton Model Perhaps the simplest randomized model for generating a sequence of message arrival times is based on an exponential distribution: messages are emitted in a probabilistic manner, so that the gap x in time between messages i and i + 1 is distributed according to the "memoryless" exponential density function f (x) = ffe-ffx, for a parameter ff > 0. (In other words, the probability that the gap exceeds x is equal to e-ffx.) The expected value of the gap in this model is ff-1, and hence one can refer to ff as the rate of message arrivals. Intuitively, a "bursty" model should extend this simple formulation by exhibiting periods of lower rate interleaved with periods of higher rate. A natural way to do this is to construct a model with multiple states, where the rate depends on the current state. Let us start with a basic model that incorporates this idea, and then extend it to the models that will primarily be used in what follows. A two-state model. Arguably the most basic bursty model of this type would be constructed from a probabilistic automaton A with two states q0 and q1, which we can think of as corresponding to "low" and "high." When A is in state q0, messages are emitted at a slow rate, with gaps x between consecutive messages distributed independently according to a density function f0(x) = ff0e-ff0x When A is in state q1, messages are emitted at a faster rate, with gaps distributed independently according to f1(x) = ff1e-ff1x, where ff1 > ff0. Finally, between messages, A changes state with probability p 2 (0, 1), remaining in its current state with probability 1 - p, independently of previous emissions and state changes. Such a model could be used to generate a sequence of messages in the natural way. A begins in state q0. Before each message (including the first) is emitted, A changes state with probability p. A message is then emitted, and the gap in time until the next message is determined by the distribution associated with A's current state. One can apply this generative model to find a likely state sequence, given a set of messages. Suppose there is a given set of n + 1 messages, with specified arrival times; this determines a sequence of n inter-arrival gaps x = (x1, x2, . . . , xn). The development here will use the basic assumption that all gaps xi are strictly positive. We can use the Bayes procedure (as in e.g. [14]) to determine the conditional probability of a state sequence q = (qi1, . . . , qin); note that this must be done in terms of the underlying density functions, since the gaps are not drawn from discrete distributions. Each state sequence q induces a density function fq over sequences of gaps, which has the form fq(x1, . . . , xn) = Qnt=1 fit(xt). If b denotes the number of state transitions in the sequence q -- that is, the number of indices it so that qit 6= qit+1 -- then the (prior) probability of q is equal to ( Y it6=it+1 p)( Yit=it+1 1 - p) = p b(1 - p)n-b = p 1 - p ! b (1 - p)n. 5. (In this calculation, let i0 = 0, since A starts in state q0.) Now, Pr [q | x] = Pr [q] fq(x)P q0 Pr [q0] fq0 (x) = 1Z p1 - p ! b (1 - p)n nY t=1 f it(xt), where Z is the normalizing constant Pq0 Pr [q0] fq0 (x). Finding a state sequence q maximizing this probability is equivalent to finding one that minimizes - ln Pr [q | x] = b ln 1 - pp ! + nX t=1 - ln f it(xt)! - n ln(1 - p) + ln Z. Since the third and fourth terms are independent of the state sequence, this latter optimization problem is equivalent to finding a state sequence q that minimizes the following cost function: c (q | x) = b ln 1 - pp ! + nX t=1 - ln f it (xt)! Finding a state sequence to minimize this cost function is a problem that can be motivated intuitively on its own terms, without recourse to the underlying probabilistic model. The first of the two terms in the expression for c (q | x) favors sequences with a small number of state transitions, while the second term favors state sequences that conform well to the sequence x of gap values. Thus, one expects the optimum to track the global structure of bursts in the gap sequence, while holding to a single state through local periods of non-uniformity. Varying the coefficient on b controls the amount of "inertia" fixing the automaton in its current state. The next step is to extend this simple "high-low" model to one with a richer state set, using a cost model; this will lead to a method that also extracts hierarchical structure from the pattern of bursts. An infinite-state model. Consider a sequence of n + 1 messages that arrive over a period of time of length T . If the messages were spaced completely evenly over this time interval, then they would arrive with gaps of size g = T /n. Bursts of greater and greater intensity would be associated with gaps smaller and smaller than g. This suggests focusing on an infinite-state automaton whose states correspond to gap sizes that may be arbitrarily small, so as to capture the full range of possible bursts. The development here will use a cost model as in the two-state case, where the underlying goal is to find a state sequence of minimum cost.
Thus, consider an automaton with a "base state" q0 that has an associated exponential density function f0 with rate ff0 = g-1 = n/T -- consistent with completely uniform message arrivals. For each i > 0, there is a state qi with associated exponential density fi having
6.
0 1 32
g ln n per state
20 1 3 tree representation
0 1 32 bursts
b)
time
optimal state sequence
a) q q q q0 1 2 3 qi
transition cost transition cost 0 emissions at rateg-1 s i
Figure 1: An infinite-state model for bursty sequences. (a) The infinite-state automaton A*s,fl; in state qi, messages are emitted at a spacing in time that is distributed according to f(x) = ffie-ffix, where ffi = g-1si. There is a cost to move to states of higher index, but not to states of lower index. (b) Given a sequence of gaps between message arrivals, an optimal state sequence in A*s,fl is computed. This gives rise to a set of nested bursts: intervals of time in which the optimal state has at least a certain index. The inclusions among the set of bursts can be naturally represented by a tree structure.
rate ffi = g-1si, where s > 1 is a scaling parameter. (i will be referred to as the index of the state qi.) In other words, the infinite sequence of states q0, q1, . . . models inter-arrival gaps that decrease geometrically from g; there is an expected rate of message arrivals that intensifies for larger and larger values of i. Finally, for every i and j, there is a cost o/ (i, j) associated with a state transition from qi to qj. The framework allows considerable flexibility in formulating the cost function; for the work described here, o/ (*, *) is defined so that the cost of moving from a lower-intensity burst state to a higher-intensity one is proportional to the number of intervening states, but there is no cost for the automaton to end a higher-intensity burst and drop down to a lower-intensity one. Specifically, when j > i, moving from qi to qj incurs a cost of (j - i)fl ln n, where fl > 0 is a parameter; and when j 0, since all gaps are positive.) If q* is an optimal state sequence in Aks,fl, then it is also an optimal state sequence in A*s,fl .
Before proceeding to the proof, here are two key points to note. First, in all the experiments here, an optimal state sequence in A*s,fl can be found by restricting to a number of states k that is a very small constant, always at most 25.
Second, some condition requiring gaps to be positive is necessary in order for the theorem to hold, as the following example shows. Suppose that x were to consist of n gaps, each equal to 0, where n is large enough that sn > nfl . Then the state sequence q(j) in which all n states are equal to qj has cost
c iq(j) | xj = j(fl ln n) - n ln fj(0) = j(fl ln n) - n ln ffj
= j(fl ln n) - nj ln s + n ln g = j(fl ln n - n ln s) + n ln g.
8.
For increasing values of j, these costs c iq(j) | xj form a sequence of negative numbers tending to -1, and hence there is no state sequence in A*s,fl that achieves a cost less than or equal to that of all others.
When all gaps are positive, however, no such example is possible, since Theorem 2.1 establishes that there is a state sequence in A*s,fl achieving the minimum cost.
Proof of Theorem 2.1. Let q* = (q`1 , . . . , q`n) be an optimal state sequence in Aks,fl, and let q = (qi1, . . . , qin) be an arbitrary state sequence in A*s,fl. As always, set `0 = i0 = 0, since both sequences start in state q0; for notational purposes, it is useful to define `n+1 = in+1 = 0 as well. The goal is to show that c (q* | x) = j0 >= j* + 1, then - ln fj00 (xt) >= - ln fj0 (x).
Since k = d1 + logs T + logs ffi(x)-1e, one has
ffk-1 = g-1sk-1 = nT * sk-1 >= 1T * slogs T +logs ffi(x)-
1 = 1
T
T ffi(x) =
1 ffi(x).
Since ffi(x)-1 >= x-1t for any t = 1, 2, . . . , n, the index k - 1 is at least as large as the j for which - ln fj(xt) is minimized. It follows that for those t for which it 6= it0 one has-
ln fi0t(xt) it0 = k - 1.
Combining these inequalities for the state transition costs and the gap costs, one obtains
c (q0 | x) =
n-1X
t=0 o/ (i
0t, i0t+1)!+ nX
t=1 - ln f
i0t(xt)! 0.
Note that although the final computation of an optimal state sequence is carried out by recourse to a finite-state model, working with the infinite model has the advantage that a number of states k is not fixed a priori; rather, it emerges in the course of the computation, and in this way the automaton A*s,fl essentially "conforms" to the particular input instance.
3 Hierarchical Structure and E-mail Streams Extracting hierarchical structure. From an algorithm to compute an optimal state sequence, one can then define the basic representation of a set of bursts, according to a hierarchical structure.
For a set of messages generating a sequence of positive inter-arrival gaps x = (x1, x2, . . . , xn), suppose that an optimal state sequence q = (qi1, qi2, . . . , qin) in A*s,fl has been determined. Following the discussion of the previous section, we can formally define a burst of intensity j to be a maximal interval over which q is in a state of index j or higher. More precisely, it is an interval [t, t0] so that it, . . . , it0 >= j but it-1 and it0+1 are less than j (or undefined if t - 1 n).
It follows that bursts exhibit a natural nested structure: a burst of intensity j may contain one or more sub-intervals that are bursts of intensity j + 1; these in turn may contain subintervals that are bursts of intensity j + 2; and so forth. This relationship can be represented by a rooted tree \Gamma , as follows. There is a node corresponding to each burst; and node v is a child of node u if node u represents a burst Bu of intensity j (for some value of j), and node v represents a burst Bv of intensity j + 1 such that Bv ` Bu. Note that the root of \Gamma corresponds to the single burst of intensity 0, which is equal to the whole interval [0, n].
Thus, the tree \Gamma captures hierarchical structure that is implicit in the underlying stream. Figure 1(b) shows the transformation from an optimal state sequence, to a set of nested bursts, to a tree.
Hierarchy in an e-mail stream. Let us now return to one of the initial motivations for this model, and consider a stream of e-mail messages. What does the hierarchical structure of bursts look like in this setting?
I applied the algorithm to my own collection of saved e-mail, consisting of messages sent and received between June 9, 1997 and August 23, 2001. (The cut-off date is chosen here so as to roughly cover four academic years.) First, here is a brief summary of this collection. Every piece of mail I sent or received during this period of time, using my cs.cornell.edu email address, can be viewed as belonging to one of two categories: first, messages consisting of one or more large files, such as drafts of papers mailed between co-authors (essentially, e-mail as file transfer); and second, all other messages. The collection I am considering here consists simply of all messages belonging to the second, much larger category; thus, to a
10.
rough approximation, it is all the mail I sent and received during this period, unfiltered by content but excluding long files. It contains 34344 messages in UNIX mailbox format, totaling 41.7 megabytes of ascii text, excluding message headers.1
Subsets of the collection can be chosen by selecting all messages that contain a particular string or set of strings; this can be viewed as an analogue of a "folder" of related messages, although messages in the present case are related not because they were manually filed together but because they are the response set to a particular query. Studying the stream induced by such a response set raises two distinct but related questions. First, is it in fact the case that the appearance of messages containing particular words exhibits a "spike," in some informal sense, in the (temporal) vicinity of significant times such as deadlines, scheduled events, or unexpected developments? And second, do the algorithms developed here provide a means for identifying this phenomenon?
In fact such spikes appear to be quite prevalent, and also rich enough that the algorithms of the previous section can extract hierarchical structure that in many cases is quite deep. Moreover, the algorithms are efficient enough that computing a representation for the bursts on a query to the full e-mail collection can be done in real-time, using a simple implementation on a standard PC.
To give a qualitative sense for the kind of structure one obtains, Figures 2 and 3 show the results of computing bursts for two different queries using the automaton A*2. Figure 2 shows an analysis of the stream of all messages containing the word "ITR," which is prominent in my e-mail because it is the name of a large National Science Foundation program for which my colleagues and I wrote two proposals in 1999-2000. There are many possible ways to organize this stream of messages, but one general backdrop against which to view the stream is the set of deadlines imposed by the NSF for the first run of the program. Large proposals were submitted in a three-phase process, with deadlines of 11/15/99, 1/5/00, and 4/17/00 for letters of intent, pre-proposals, and full proposals respectively. Small proposals were submitted in a two-phase process, with deadlines of 1/5/00 and 2/14/00 for letters of intent and full proposals respectively. I participated in a group writing a proposal of each kind.
Turning to the figure, part (a) is a plot of the raw input to the automaton A*2, showing the arrival time of each message in the response set. Part (b) shows a nested interval representation of the set of bursts for the optimal state sequence in A*2; the intervals are annotated with the first and last dates of the messages they contain, and the dates of the NSF deadlines are lined up with the intervals that contain them. Note that this is a schematic representation, designed to show the inclusions that give rise to the tree \Gamma ; the lengths and centering of the intervals in the drawing are not significant. Part (c) shows a drawing of the resulting tree \Gamma . The root corresponds to the single burst of intensity 0 that is present in any state sequence. One sees that the two children of the root span intervals surrounding the
1These figures reveal that I receive less e-mail per day than many of my colleagues; one contributing factor is that I do not subscribe to any high-volume mailing lists based outside Cornell.
11.
2/1410/28-2/21/0010/28/99-
11/1610/28- 11/1611/2- 11/15
11/9-
7/10/00-10/31/00 7/10-7/14
1/2-2/4 1/2-1/5
0 20 40 60 80 100 120 140
1.4e+06 1.5e+06 1.6e+06 1.7e+06 1.8e+06 1.9e+06 2e+06 2.1e+06 2.2e+06 2.3e+06 2.4e+06 2.5e+06 a)
c)
Minutes since 1/1/97
Message #
b)
2/14
10/28 11/16 1/2/00
11/16 11/15
11/2 11/9
2/4 7/10
2/21
7/10
7/14 10/31
10/28/9910/28
(large proposals) 11/15: letter of intent deadline
2/14: full proposal deadline
0 1 2 3 4 5
1/2 1/5
1/5: pre-proposal deadline (large proposals)
4/17: full proposal deadline(large proposals)
7/11: unofficial notification
9/13: official announcementof awards
intensities
(small proposals) (small proposal)
Figure 2: The stream of all messages containing the word "ITR," analyzed using the automaton A*2. (a) The raw input data: the x-axis shows message arrival time; the y-axis shows message sequence number. (b) The set of bursts in the optimal state sequence for A*2, drawn schematically to show the inclusions that form the tree \Gamma . (Lengths of intervals are standardized and hence not to scale.) Intervals are annotated with starting and ending dates, and the dates of the NSF ITR program deadlines are lined up with the intervals that contain them. (c) A representation of the tree \Gamma , showing inclusions among the bursts.
submission deadlines and notification dates, respectively. Moreover, the sub-tree rooted at the first of these children splits further into two sub-trees that are concentrated over a week leading up to the deadline for letters of intent (11/15/99), and four days leading up to the pre-proposal deadline (1/5/00). Finally, note that there is no burst of positive intensity over the final deadline for large proposal, since we did not continue our large submission past the pre-proposal stage.
Figure 3 shows an analysis of the stream of all messages containing the word "prelim," which is the term used at Cornell for (non-final) exams in undergraduate courses. One sees that the raw data in this example (part (a) of the figure) exhibits an arguably more regular structure than in the previous example. I taught undergraduate courses in four of the eight semesters covered by the collection of e-mail, and each of these courses had two prelims.
12.
prelim 24/11/00 prelim 12/24/00 prelim 24/15/99 prelim 12/25/99
11/13/00prelim 2
1 2 3 40 5 6 7 8
prelim 110/4/00 intensities 0 50 100 150 200 250 300 350 400
200000 400000 600000 800000 1e+06 1.2e+06 1.4e+06 1.6e+06 1.8e+06 2e+06 2.2e+06 2.4e+06
Minutes since 1/1/97
Message #
a)
c)
b)
Figure 3: The stream of all messages containing the word "prelim," analyzed using the automaton A*2. Parts (a), (b), and (c) are analogous to Figure 2, but date annotations are omitted. In part (b), the dates of prelims (exams) are lined up with the intervals that contain them.
For the first of these courses, correspondence with students was restricted almost exclusively to a special course e-mail account, and hence very little appears in my own saved e-mail. The remaining three courses are captured very cleanly by the tree \Gamma computed from the optimal state sequence of A*2 (parts (b) and (c) of the figure) -- each course corresponds to a long burst, and each contains two shorter, more intense bursts for the particular prelims. Specifically, the three children of the root are centered over the semesters in which the three undergraduate courses were taught (Spring 1999, Spring 2000, and Fall 2000); and the subtrees below these children split further into two sub-trees each, concentrated either directly over or slightly preceding the two prelims given that semester.
Overall, these structures suggest how a large folder of e-mail might naturally be divided into a hierarchical set of sub-folders around certain key events, based only on the rate of message arrivals. The appropriateness of Forster's comments on the time-sense in narratives is also fairly striking here: when organized by burst intensities, the period of time covered
13.
in the e-mail collection very clearly "piles up into a few notable pinnacles" [17], rather than proceeding uniformly.
4 Enumerating Bursts Given a framework for identifying bursts, it becomes possible to perform a type of enumeration: for every word w that appears in the collection, one computes all the bursts in the stream of messages containing w. Combined with a method for computing a weight associated with each burst, and for then ranking by weight, this essentially provides a way to find the terms that exhibit the most prominent rising and falling pattern over a limited period of time. This can be applied to e-mail, and it can be done very efficiently even on the scale of the e-mail corpus from the previous section; roughly speaking, it can be performed in a single pass over an inverted index for the collection. Here, however, I consider a different application of this technique: extracting bursts in term usage from the titles of conference papers. Two distinct sources of data will be used here: the titles of all papers from the database conferences SIGMOD and VLDB for the years 1975-2001; and the titles of all papers from the theory conferences STOC and FOCS for the years 1969-2001.
The first issue that must be addressed concerns the underlying model: unlike e-mail messages, which arrive continuously over time, conference papers appear in large batches -- essentially, twenty to sixty new papers appear together every half year. As a result, the automaton A*s,fl is not appropriate, since it is fundamentally based on analyzing the distribution of inter-arrival gaps. Instead, one needs to model a related kind of phenomenon: documents arrive in discrete batches; in each new batch of documents, some are relevant (in the present case, their titles contain a particular word w) and some are irrelevant. The idea is thus to find an automaton model that generates batched arrivals, with particular fractions of relevant documents. A sequence of batched arrivals could be considered bursty if the fraction of relevant documents alternates between reasonably long periods in which the fraction is small and other periods in which it is large.
Suppose there are n batches of documents; the tth batch contains rt relevant documents out of a total of dt. Let R = Pnt=1 rt and D = Pnt=1 dt. Now, define an automaton B*s,fl as follows, by close analogy with the construction of A*s,fl. For each state qi of B*s,fl , for i >= 0, there is an expected fraction of relevant documents pi. Set p0 = p = R/D, and pi = p0si. Since it does not make sense for pi to exceed 1, the state qi will only be defined for i such that pi = 1; thus, B*s,fl will be a finite-state automaton. One can further restrict B*s,fl to k states, resulting in the automaton Bks,fl. Viewed in a generative fashion, one can imagine state qi in these models as producing a mixture of relevant and irrelevant documents according to a binomial distribution with probability pi.
The cost of a state sequence q = (qi1, . . . , qin) in B*s,fl is defined as follows. If the automa14.
Word Interval of burst data 1975 SIGMOD -- 1979 SIGMOD base 1975 SIGMOD -- 1981 VLDB application 1975 SIGMOD -- 1982 SIGMOD bases 1975 SIGMOD -- 1982 VLDB design 1975 SIGMOD -- 1985 VLDB relational 1975 SIGMOD -- 1989 VLDB model 1975 SIGMOD -- 1992 VLDB large 1975 VLDB -- 1977 VLDB schema 1975 VLDB -- 1980 VLDB theory 1977 VLDB -- 1984 SIGMOD distributed 1977 VLDB -- 1985 SIGMOD data 1980 VLDB -- 1981 VLDB statistical 1981 VLDB -- 1984 VLDB database 1982 SIGMOD -- 1987 VLDB nested 1984 VLDB -- 1991 VLDB deductive 1985 VLDB -- 1994 VLDB transaction 1987 SIGMOD -- 1992 SIGMOD objects 1987 VLDB -- 1992 SIGMOD object-oriented 1987 SIGMOD -- 1994 VLDB parallel 1989 VLDB -- 1996 VLDB object 1990 SIGMOD -- 1996 VLDB mining 1995 VLDB -- server 1996 SIGMOD -- 2000 VLDB sql 1996 VLDB -- 2000 VLDB warehouse 1996 VLDB -- similarity 1997 SIGMOD -- approximate 1997 VLDB -- web 1998 SIGMOD -- indexing 1999 SIGMOD -- xml 1999 VLDB --
Figure 4: The 30 bursts of highest weight in B22, using titles of all papers from the database conferences SIGMOD and VLDB, 1975-2001.
ton is in state qi when the tth batch arrives, a cost of
oe(i, t) = - ln "dtr
t!p
rti (1 - pi)dt-rt#
is incurred, since this is the negative logarithm of the probability that rt relevant documents would be generated using a binomial distribution with probability pi. There is also a cost of o/ (it, it+1) associated with the state transition from qit to qit+1 , where this cost is defined precisely as for A*s,fl. A state sequence of minimum total cost can then be computed as in Section 2.
In the analysis of conference paper titles here, the main goal is to enumerate bursts of
15.
Word Interval of burst grammars 1969 STOC -- 1973 FOCS automata 1969 STOC -- 1974 STOC languages 1969 STOC -- 1977 STOC machines 1969 STOC -- 1978 STOC recursive 1969 STOC -- 1979 FOCS classes 1969 STOC -- 1981 FOCS some 1969 STOC -- 1980 FOCS sequential 1969 FOCS -- 1972 FOCS equivalence 1969 FOCS -- 1981 FOCS programs 1969 FOCS -- 1986 FOCS program 1970 FOCS -- 1978 STOC on 1973 FOCS -- 1976 STOC complexity 1974 STOC -- 1975 FOCS problems 1975 FOCS -- 1976 FOCS relational 1975 FOCS -- 1982 FOCS logic 1976 FOCS -- 1984 STOC vlsi 1980 FOCS -- 1986 STOC probabilistic 1981 FOCS -- 1986 FOCS how 1982 STOC -- 1988 STOC parallel 1984 STOC -- 1987 FOCS algorithm 1984 FOCS -- 1987 FOCS graphs 1987 STOC -- 1989 STOC learning 1987 FOCS -- 1997 FOCS competitive 1990 FOCS -- 1994 FOCS randomized 1992 STOC -- 1995 STOC approximation 1993 STOC -- improved 1994 STOC -- 2000 STOC codes 1994 FOCS -- approximating 1995 FOCS -- quantum 1996 FOCS --
Figure 5: The 30 bursts of highest weight in B22, using titles of all papers from the theory conferences STOC and FOCS, 1969-2001.
positive intensity, but not to emphasize hierarchical structure. Thus, the two-state automaton B22 is used; given an optimal state sequence, bursts of positive intensity correspond to intervals in which the state is q1 rather than q0. For such a burst [t1, t2], we can define the weight of the burst to be
t2X
t=t1(oe(0, t) - oe(1, t)). In other words, the weight is equal to the improvement in cost incurred by using state 1 over the interval rather than state 0. Observe that in an optimal sequence, the weight of every burst is non-negative. Intuitively, then, bursts of larger weight correspond to more prominent periods of elevated activity. (This notion of weight can be naturally extended to
16.
larger numbers of states, as well as to the automaton model from Section 2.)
In Figure 4, this framework is applied to the titles of SIGMOD and VLDB papers for the years 1975-2001. For each word w (including stop-words), an input to B22 is constructed in which rt is the number of titles at the tth conference (chronologically) that contain the word w, and dt is the total number of titles at the tth conference. The 30 bursts with the highest weight, over all possible words w, are then depicted in the figure, sorted by year of appearance. The bursts with no given ending date (`mining', `warehouse', `similarity', `approximate', `web', `indexing', and `xml') are those for which the interval extends to the most recent conference, suggesting terms that are in the middle of a large-weight burst at present. Note that no pre-processing is done on the titles, other than to convert each word to lower-case. One observes that the words in Figure 4 are almost all quickly recognizable as carrying technical content, even though they are the top results in an enumeration where bursts were computed and ranked for all words, including stop-words.2
Figure 5 shows the results of the same computation on the titles of STOC and FOCS papers for the years 1969-2001. For both these collections, it is important to note that the number of occurrences of a word w is in general a quantity that, at a local scale, changes very rapidly from one conference to the next; thus, many of the intervals depicted in the figures span conferences in which the indicated word did not appear at all, and omit ones with large numbers of occurrences. The non-trivial cost of state transitions in B22 is crucial in making it possible for intervals of any reasonable length to form in the presence of this data.
5 Related Work The Topic Detection and Tracking (TDT) study [2, 3, 61, 62] articulated the problem of extracting significant topics and events from a stream of news articles, thereby framing the type of document stream analysis questions considered here. Much of the emphasis in the TDT study was on techniques for the on-line version of the problem, in which events must be detected in real-time; but there was also a retrospective version in which the whole stream could be analyzed. Similar issues have recently been addressed in the visualization community [26, 43, 60], where the problem of visualizing the appearance and disappearance of themes in a sequence of news stories has been explored.
Following on the TDT work, Swan, Allan, and Jensen [56, 57, 58] developed a method for constructing overview timelines of a set of news stories. For each named entity and noun phrase in the corpus, they perform a O/2 test to identify days on which the number of occurrences yields a value above a certain threshold; contiguous sets of days meeting this condition are then grouped into an interval that is added to the timeline. Thus, the high-level structure of their approach is parallel to the enumerative method in Section 4. However, the
2The bursts for `data,' `base,' and `bases' in the years 1975-1981 arise in large part from the fact that the term "database" was written as two words in a significant number of the paper titles during this period.
17.
underlying methodology is quite different from the present work in two key respects. First, Swan et al. note that the use of thresholds makes it difficult to construct long intervals of activity for a single feature -- such intervals are often broken apart by brief gaps in which the feature does not occur frequently enough, and subsequent heuristics are needed to piece them together. The present work, by modeling a burst as a state transition with costs, allows for a long interval to naturally persist across such gaps; essentially, in place of thresholds, the optimization problem inherent in finding a minimum-cost state sequence adaptively groups nearby high-intensity intervals together when it is advantageous to do so. Second, the work of Swan et al. does not attempt to infer any type of hierarchical structure in the appearance of a feature.
Lewis and Knowles analyze the dynamics of message-sending over a very short time scale, searching for features that can determine whether one message is a response to another [37]. This is applied to develop robust techniques for identifying threads, a popular metaphor for organizing e-mail and newsgroup postings [15, 22]. In a very different context, Grosz and Sidner develop structural models for discourse as a means of analyzing communication [21]; their use of stack models in particular results in a nested organization that bears an intriguing, though distant, relationship to the nested structure of bursts studied here.
The present work clearly overlaps with the large areas of time series analysis and sequence mining [10, 25]; connections to related probabilistic frameworks such as bursty on-off sources [32] and hidden Markov models [48] have already been discussed above. Ehrich and Foith [16] proposed a method for constructing a tree from a one-dimensional time series, essentially by introducing a branch-point at each local minimum and a leaf at each local maximum (see also [55]). In the context of the applications here, such an approach would yield trees of enormous complexity, due to the ruggedness of the underlying temporal data, with many local minima and maxima.
The search for a minimum-cost state sequence in the automata of Section 2 and 4 can also be viewed as a search for approximate level sets in a time series, and hence related to the large body of work on piece-wise function approximation in both statistics and data mining (see e.g. [23, 24, 27, 31, 33, 35, 41]). In a discrete framework, work on mining episodes and sequential patterns (e.g. [1, 12, 25, 40]) has developed algorithms to identify particular configurations of discrete events clustered in time, in some cases obeying partial precedence constraints on their order. Finally, there is an interesting general relationship to work on traffic analysis in the areas of cryptography and security [52]; in that context, temporal analysis of a message stream is crucial because the content of the messages has been explicitly obscured.
6 Extensions and Conclusions In the settings discussed above, the analysis has made use of both the temporal information and the underlying content. The role of temporal data is clear; but the content of course
18.
plays an integral role as well: Section 3 deals with streams consisting of the response set for a particular query to a larger stream; and Section 4 considers streams with batched arrivals, in which a particular subset of each batch is designated as relevant. And in fact, there is strong evidence that the interplay between content and time is crucial here -- that an arbitrary set of messages with same sequence of arrival times would not exhibit an equally strong set of bursts. Adapting a permutation test from Swan and Jensen [58], one can start with a complete e-mail corpus having arrival times t1, t2, . . . , tN , choose a random permutation ss, and shuffle the corpus so that message ss(i) arrives at time ti (instead of message i), for i = 1, 2, . . . , N . The resulting shuffled corpus has the same set of arrival times and the same messages, but the original correspondence between the two is broken; do equivalently strong "spurious" bursts appear in this new sequence? In fact, they clearly do not: when the weight of bursts for all words (with respect to A*2) is computed using the e-mail corpus in Section 3, the total weight associated with the true corpus is more than an order of magnitude greater than the average total weight over 100 randomly shuffled versions (369,980 versus 25,141). Moreover, the shuffled versions exhibit almost no non-trivial hierarchical structure; the average total number of words generating bursts of intensity at least 2 (i.e. inducing trees \Gamma with two or more levels below the root) is 16.7 over the randomly shuffled versions, compared with 3865 in the true corpus.
I have also applied the overall framework developed here to Web clickstream data collected by Gay et al. [18]. The dataset in [18] was compiled as part of a study of student usage of wireless laptops: The browser clicks of roughly 80 undergraduate students in two particular classes at Cornell were collected (with consent) from wireless laptops over a period of two and a half months in Spring 2000. Bursts with respect to A*s,fl can be computed by an enumerative method, as in Section 4: for every URL w, all bursts in the stream of visits to w are determined; the full set of bursts is then ordered by weight. Each burst, associated with a URL w, now has an additional quantity associated with it: the number of distinct users who visited w during the interval of the burst. This allows one to distinguish between collective activity involving much of the class and that of just a single user. As it turns out, if one focuses on bursts that involve at least 10 distinct users, then many of those with the highest weight involve the URLs of the on-line class reading assignments, centered on intervals shortly before and during the weekly sessions at which they were discussed.
A final observation is that the use of a model based on state transitions leads to bursts with sharp boundaries; they have clear beginnings and ends. In particular, this means that for every burst, one can identify a single message on which the associated state transition occurred. This is akin to the TDT study's notion of (retrospective) first story detection [2], although in the automaton model of the present work, identifying initial messages does not constitute a separate problem since it follows directly from the definition of the state transitions. In the context of e-mail, the contents of such an initial message can often serve as a concentrated summary of the circumstances precipitating the burst -- in other words, there is frequently something in the message itself to frame the flurry of message19.
sending that is about to occur. And for messages on which bursts for several different terms are initiated simultaneously, this phenomenon is even more apparent; such messages often represent natural "landmarks" at the beginning of a long-running episode.
In many domains, we accumulate extensive and detailed records of our own behavior -- in the e-mail we send and receive, the Web pages we visit, the queries we issue to search engines. An underlying theme, of which several aspects have been developed here, is that a great number of these settings have a fundamental temporal aspect; they are punctuated by the sharp and sudden onset of particular episodes, and can be organized around rising and falling patterns of activity. There is a great amount of complexity underpinning such a picture. But by developing a better understanding of it, one can hope ultimately to find structure in the raw data that we generate through the basic process of interacting and communicating.
Acknowledgements. I thank Lillian Lee for valuable discussions and suggestions throughout the course of this work.
IMAP (Internet Message Access Protocol) was designed to centralize email information, I believe. If stored/implemented with a database, what more would you need ?
I think querying through SQL would satisfy most of us.. and be very useful in corporate environments (for example, query all email sent from a user to support), and it's already done by some projects like DBMAIL.
Anybody out there with experience using these ?
BTW, there's an extensive database of IMAP products including some that make the data accessible via LDAP... hours of fun!
Notepad specialist & FAT administrator, group training available
Now we all now that most email is delivered promptly by gremlins, but gremlins are hungry and will eat a few bytes here and there.
They also leave waste in the form of spam.
So, I propose that we turn to gnomes to deliver the mail instead, as they are much cleaner, and can be satiated by attaching a file like 'Hamburger.txt'.
"I only speak the truth"
Karma: null(Mostly affected by an unassigned variable)
Every time you sign up for some mailing list or discussion group, create a new e-mail account or alias for just those mailings. Bam, it's automatically sorted out by itself with extreme ease. If you have limited bandwith (or are checking, say, on your palm) sometimes, just check your important addresses frequently, and reserve your mailing lists for a once-per-day check.
If some site asks for your e-mail address to download a piece of software, or to register, make up a new alias and give that to them. If you start getting tons of crap at that address, you can just remove that alias, and they get it all bounced back in their stupid spamming faces.
Give one address to your cow-orkers just for work stuff. Give a different one to your Mom and other techno-nots that blocks all attachments. Give another one to your friends with brains that goes unfiltered. For people you don't want to talk to, give them the address of an autoresponder tied to Eliza.
Be a *Happy Camper* and let your addresses be *Bubbles* and you be just *You*.
... "Give me a woman who loves beer and I will conquer the w
there is no thing
what else could you want?
MT93V - GXPJQ - W4HQ3 - DV2Q7 - 8G64Y
TQ4CV - XPJR3 - KPG3Q - HGH74 - BMYWT
VXKC4 - 2B3YF - W9MFK - QB3DB - 9Y7MB
F6PGG - 4YYDJ - 3FF3T - R328P - 3BXTG
WFX8X - J8FHX - RY234 - RBPPB - QZWBM
F2T26 - BMK6H - 69QX8 - FYV8D - TY4CM
RWRTK - 2RRQC - C4RHF - C7BQF - WP6TB
RM233 - 2PRQQ - FR4RH - JP89H - 46QYB
Enjoy!
--
pants ahoy
I say could have because it got sucked down the drain in late 2000 with all of the companies that didn't have a damn thing to offer. Lesson #1: make sure your CEO gets along with your venture partner.
No, I'm not bitter. Much.
a nice methods paper, but mr. kleinberg doesn't use any of the free metadata that comes with email and news: to, from, subject.
i use outlook, and cluster my mail by sender... most of the time, that tells me pretty easily whether a given piece of mail is a work email, a personal email or a mailing list. from there, i check the subject line of work emails, just to confirm my categorization of work/humor/administrivia.
i'd want to see a comparison between a metadata-only method (rules and filters on the RFC 822 header) and mr. kleinberg's method before i'd consider using it.
It's more general than e-mail, but in the wearable computing community, there's a little application called Remembrance Agent, written by Bradley Rhodes that many folks use. In terms of stand-alone UI, it's still quite primitive, but that's because it was built around dynamic hooks into Emacs.
I've been playing around with some Java-based wrapper code, to wrap the ra-retrieve executable in a Server and allow clients to access the data via sockets. I have a Java-based client coded up that hooks into the System clipboard, but it's still in alpha-mode. All GPL'd of course, but needs a little time to mature. It's a proof-of-concept, work in progress. :-)
Check out Brad's site for more insight into the work he did and is doing.
--The more you know, the less you know.
my $pr0n = "adult";
...
my $spam = "viagra";
my $urgent = "penis enlargement";
open (INBOX,/home/mail) or die "Damn! No fun for me:$!\n";
@list = readdir(INBOX);
foreach $ (@list) {
if (-f $spam) {
my $status = unlink($spam);
}
if (-f $pr0n) {
my @MUST_SEE = $pr0n;
next;
}
if (-f $viagra) {
my @RAINY_DAY = $viagra;
next;
}
}
# or something like that
OK, it's not a piece of Linux software, but it is a beautful idea:
http://www.creo.com/sixdegrees/
668: Neighbour of the Beast
Here is a PDF version.
Boy could I use the Karma!
I sincerely hope that their first act will be to impose sanctions on Israel, take the whole Israeli cabinet to court for war crimes, and install an interim non-apartheid government.
And if Israel does not cooperate, I suggest dismantling the state entirely, and shipping its population to Texas. It's a lot safer place to live anyway.
Hoo boy. Here we go again. When are you kids going to get it straight?
- Choosing not to listen to somebody is *not* censorship.
- Throwing your mail away before you open it is *not* censorship.
- Choosing not to relay somebody's spam is *not* censorship.
- Choosing not to broadcast somebody's TV program, even if you own a TV network, is *not* censorship.
- Telling a movie producer you won't distribute his/her movie unless he/she makes cuts or changes to the subject matter is *not* censorship.
- Rallying your church group together to burn books is *not* censorship.
- Refusing to sell certain magazines or newspapers, if you own a newsstand, is *not* censorship.
The only way somebody can be truly "censored" is when there is no legal means for that person to get his/her speech/art/etc. produced and disseminated to the pubic. Generally speaking, the only body with that type of power is the government -- because they make the laws.
Everything else is merely an inconvenience. It may piss you off, sure, and you may wish things were different. But you can't force people to support you, encourage you, or fund you if they just don't want to. For example, people in this country (the US) *do* have a right to decide what material constitutes pornography, relative to their local community standards -- and if you don't like it, you are within your rights to move to another town.
"No censorship" does not mean being forced to look at every piece of crap that somebody wants to throw in your face, and god help us if it did.
Breakfast served all day!
Now I can automatically filter my barely-legal porn spam from my anime porn spam. Lets hear it for technology =)
Somewhat to my astonishment when I clicked on the link up popped a box asking me to confirm Postscript Renderer options! I had no idea that I had anything on this box that could read Postscript.
Some minutes of 100% CPU later up pops a PSP window, with the document rendered in a font about five pixels square. Fair enough, I suppose, for what's basically a photograph editing application.
But really, how bizarre, posting something in a low level printer file format. We'll have people posting documents in PCL5 next.
First, I sort out mail from the mailingslists I read.
Then, mail from friends, and people I correspond with a lot.
Finally, I have a weighted scoring recipe:
:0 Bh
* -199^0
#Assign an initial value of -199, mail gets filtered, if the score is above 0, at the end of the recipe.
* 50^1 ^(From|To):.*@hotmail.com
* 50^1 ^(From|To):.*@yahoo.com
* 50^1 ^(From|To):.*@aol.com
* 50^1 ^(From|To):.*@msn.com
* 50^1 ^(From|To):.*@excite.com
* 50^1 ^(From|To):.*@netscape.net
* 50^1 ^(From|To):.*@yahoo.co.uk
#Most mail to and from these domains is spam, so score it.
* 100^1 opt-out
* 50^1 opt-in
* 200^1 OTCBB
* 50^1 viagra
* 50^1 zyban
* 50^1 propecia
* 75^1 FREE
* 75^1 GUARANTEED
* 75^1 LEGAL
* 50^2 MILLIONAIRE
* 50^1 100%
#Words I only see in spam.
mail/Trash
This works quite well for me. If any spam gets through, I try to find some words, that I don't get in normal mail, and add them to the scoring.
/Styx
Message rules are very easy to set up and manage. No agents.
LNB Mission crazy undulate coelacanth memory Mission culto Ploopo memory Mission
monkey crazy memory tristan monkey LNB donkey LNB donkey donkey donkey
LNB crazy donkey Mission tristan tristan tristan Ploopo monkey scoopula Mission
Mission monkey donkey memory Ploopo crazy bubble Ploopo Ploopo scoopula donkey
culto monkey donkey coelacanth bubble donkey frib monkey crazy undulate Mission
undulate discontent Ploopo LNB coelacanth discontent Mission discontent undulate vagina culto
Ploopo frib tristan frib Ploopo Ploopo Ploopo Ploopo memory discontent coelacanth
memory memory bubble vagina frib crazy LNB culto Ploopo discontent memory
coelacanth undulate scoopula frib memory vagina crazy frib scoopula culto Ploopo
LNB tristan memory scoopula bubble tristan donkey donkey scoopula tristan coelacanth
culto Mission monkey discontent tristan coelacanth Ploopo monkey tristan monkey crazy
Mission Mission donkey crazy memory bubble bubble crazy Ploopo coelacanth Mission
crazy Mission coelacanth culto bubble donkey culto memory tristan discontent donkey
LNB coelacanth undulate undulate LNB undulate culto Ploopo discontent memory scoopula
coelacanth vagina frib coelacanth bubble Ploopo bubble undulate monkey bubble culto
bubble Mission memory undulate Mission crazy scoopula culto Ploopo Ploopo crazy
scoopula Ploopo Ploopo scoopula crazy memory vagina LNB LNB monkey bubble
discontent bubble bubble coelacanth discontent culto Mission Mission monkey tristan memory
LNB coelacanth memory Ploopo tristan Mission LNB monkey memory discontent memory
vagina scoopula Ploopo memory monkey scoopula memory Ploopo memory donkey LNB
monkey bubble tristan donkey frib vagina bubble memory vagina vagina undulate
Mission tristan discontent Mission coelacanth LNB LNB tristan scoopula coelacanth undulate
memory memory discontent tristan monkey Mission Ploopo LNB vagina discontent bubble
vagina discontent Mission tristan undulate bubble memory bubble undulate donkey culto
Mission crazy culto undulate LNB frib memory donkey culto undulate LNB
memory tristan Ploopo undulate scoopula coelacanth undulate tristan tristan frib culto
culto frib coelacanth Ploopo crazy vagina bubble undulate tristan donkey undulate
Mission frib Ploopo vagina bubble culto LNB culto donkey tristan bubble
Ploopo tristan monkey donkey LNB bubble Ploopo scoopula crazy bubble monkey
monkey bubble donkey coelacanth frib scoopula crazy crazy vagina undulate monkey
LNB frib bubble tristan Ploopo frib frib Mission memory undulate Mission
memory donkey memory crazy tristan LNB tristan frib undulate coelacanth LNB
monkey discontent bubble tristan LNB crazy memory crazy bubble coelacanth culto
monkey tristan memory scoopula coelacanth donkey LNB memory bubble bubble scoopula
Ploopo vagina culto LNB discontent Mission tristan discontent scoopula Mission memory
frib memory crazy bubble tristan LNB vagina scoopula discontent LNB donkey
coelacanth vagina Mission coelacanth coelacanth crazy discontent scoopula vagina crazy monkey
Ploopo vagina tristan Ploopo LNB donkey scoopula undulate bubble culto Ploopo
vagina Ploopo memory discontent memory frib bubble coelacanth scoopula donkey crazy
monkey scoopula crazy memory culto culto crazy memory undulate frib Mission
LNB culto undulate monkey undulate scoopula scoopula crazy LNB memory tristan
coelacanth discontent scoopula discontent vagina scoopula frib crazy crazy tristan frib
Ploopo discontent tristan vagina frib tristan tristan discontent coelacanth LNB undulate
memory Ploopo monkey LNB monkey vagina donkey monkey scoopula coelacanth discontent
crazy crazy culto crazy LNB LNB coelacanth tristan coelacanth donkey discontent
coelacanth scoopula bubble crazy crazy undulate undulate donkey Ploopo frib monkey
frib scoopula Mission Ploopo scoopula Ploopo Mission tristan bubble tristan donkey
culto tristan Mission vagina donkey culto tristan bubble memory monkey bubble
crazy LNB undulate discontent discontent monkey discontent monkey discontent frib discontent
scoopula vagina coelacanth Mission monkey frib crazy undulate Mission vagina scoopula
scoopula LNB Ploopo LNB discontent tristan memory monkey monkey Ploopo frib
scoopula Mission discontent Mission vagina donkey Ploopo bubble memory tristan culto
tristan Mission Mission tristan scoopula culto memory culto coelacanth culto tristan
LNB donkey vagina tristan donkey scoopula undulate frib discontent bubble undulate
vagina frib donkey Mission LNB memory coelacanth bubble frib culto monkey
LNB culto donkey undulate coelacanth donkey vagina bubble vagina frib bubble
crazy donkey tristan coelacanth Ploopo scoopula scoopula donkey tristan vagina discontent
culto donkey memory discontent vagina tristan LNB discontent tristan discontent frib
tristan culto discontent Mission Ploopo frib monkey bubble tristan memory LNB
crazy monkey discontent scoopula tristan Mission vagina LNB Ploopo tristan vagina
LNB culto Mission tristan coelacanth LNB culto undulate scoopula vagina discontent
vagina tristan monkey undulate Mission frib LNB monkey crazy crazy coelacanth
vagina donkey frib culto coelacanth Ploopo discontent monkey discontent culto Mission
undulate Mission LNB Mission Ploopo coelacanth donkey coelacanth Ploopo LNB bubble
Ploopo discontent LNB frib frib vagina monkey scoopula tristan bubble frib
crazy monkey frib Ploopo monkey Ploopo culto bubble discontent vagina coelacanth
LNB bubble tristan tristan memory frib culto monkey memory scoopula Ploopo
coelacanth vagina Ploopo scoopula vagina frib coelacanth monkey bubble tristan memory
Ploopo Mission vagina discontent vagina scoopula scoopula culto tristan monkey Ploopo
scoopula culto memory LNB memory discontent undulate discontent vagina memory culto
discontent monkey coelacanth bubble coelacanth undulate Ploopo Mission scoopula crazy tristan
scoopula LNB bubble tristan LNB LNB discontent undulate coelacanth memory LNB
frib Mission Ploopo tristan Mission crazy frib Mission bubble memory coelacanth
vagina bubble culto discontent Mission culto discontent coelacanth Ploopo tristan donkey
culto vagina coelacanth crazy undulate donkey memory crazy donkey frib monkey
coelacanth Mission donkey coelacanth monkey bubble tristan Mission undulate Ploopo vagina
undulate scoopula discontent monkey coelacanth bubble monkey frib bubble vagina vagina
coelacanth donkey vagina donkey Mission donkey monkey Ploopo LNB LNB crazy
memory scoopula monkey frib memory Mission Ploopo donkey vagina scoopula undulate
donkey monkey crazy discontent LNB donkey culto tristan undulate coelacanth scoopula
culto coelacanth tristan donkey vagina LNB frib scoopula monkey vagina discontent
bubble donkey frib Ploopo frib crazy crazy coelacanth donkey coelacanth tristan
bubble monkey LNB LNB vagina Mission culto donkey Mission Mission crazy
Mission coelacanth frib crazy memory donkey coelacanth undulate monkey donkey frib
tristan donkey LNB culto vagina memory Mission crazy scoopula coelacanth Ploopo
undulate vagina Mission memory memory culto monkey coelacanth tristan scoopula Mission
donkey undulate tristan culto discontent culto culto donkey crazy coelacanth donkey
culto Mission culto Ploopo scoopula monkey vagina coelacanth undulate coelacanth culto
donkey memory tristan vagina vagina coelacanth vagina culto scoopula undulate discontent
scoopula LNB culto vagina culto coelacanth memory scoopula LNB discontent donkey
Mission crazy bubble tristan frib memory scoopula LNB coelacanth LNB donkey
culto Mission memory vagina bubble discontent coelacanth discontent discontent bubble undulate
tristan vagina donkey coelacanth Ploopo memory donkey Ploopo Mission crazy tristan
crazy monkey vagina memory crazy monkey scoopula frib bubble coelacanth undulate
culto monkey frib memory scoopula monkey monkey coelacanth Ploopo LNB undulate
undulate memory vagina LNB coelacanth monkey bubble culto vagina undulate monkey
scoopula donkey bubble coelacanth culto bubble Ploopo frib crazy frib monkey
scoopula discontent tristan scoopula crazy culto coelacanth culto tristan discontent donkey
tristan undulate bubble tristan Ploopo crazy monkey discontent monkey scoopula Mission
bubble undulate discontent tristan memory crazy LNB scoopula culto Mission Mission
frib donkey Ploopo Ploopo memory donkey LNB monkey memory tristan scoopula
undulate tristan donkey donkey bubble donkey tristan discontent vagina vagina crazy
vagina donkey vagina tristan coelacanth coelacanth donkey undulate memory memory vagina
crazy tristan undulate memory crazy discontent Mission crazy undulate coelacanth scoopula
culto frib donkey culto bubble discontent coelacanth frib LNB monkey coelacanth
donkey vagina crazy undulate discontent bubble LNB coelacanth bubble tristan donkey
memory bubble donkey vagina Mission undulate culto culto vagina tristan undulate
frib bubble tristan Ploopo crazy undulate coelacanth vagina memory coelacanth LNB
tristan tristan bubble crazy coelacanth bubble frib undulate bubble undulate vagina
culto culto memory crazy Ploopo Mission culto monkey discontent tristan discontent
crazy vagina donkey tristan scoopula Ploopo scoopula bubble crazy Mission frib
coelacanth memory Mission monkey vagina scoopula LNB monkey crazy Mission Mission
vagina LNB tristan scoopula frib culto Mission discontent coelacanth culto memory
Mission monkey crazy tristan undulate coelacanth Ploopo culto memory Mission memory
Mission coelacanth Ploopo tristan bubble bubble undulate Mission vagina tristan bubble
culto LNB bubble Ploopo frib discontent vagina Mission scoopula memory tristan
undulate discontent discontent discontent bubble Ploopo undulate coelacanth frib Ploopo Mission
monkey Ploopo frib Mission memory Mission tristan crazy vagina monkey LNB
memory bubble coelacanth bubble undulate crazy Ploopo undulate coelacanth monkey bubble
undulate culto LNB coelacanth coelacanth bubble undulate discontent LNB vagina crazy
tristan tristan crazy memory memory monkey donkey coelacanth crazy undulate LNB
culto culto monkey LNB crazy vagina vagina memory frib monkey Mission
coelacanth Ploopo donkey undulate donkey LNB frib vagina bubble undulate vagina
Mission donkey donkey culto tristan Mission coelacanth culto Mission undulate Ploopo
tristan frib tristan donkey undulate coelacanth donkey culto frib culto frib
culto Ploopo undulate Ploopo scoopula vagina Ploopo coelacanth Ploopo memory tristan
coelacanth tristan undulate crazy coelacanth LNB Ploopo undulate LNB tristan crazy
bubble discontent donkey culto discontent Mission Mission Mission Mission culto Ploopo
Ploopo culto frib culto tristan crazy vagina memory undulate crazy crazy
undulate monkey bubble monkey LNB scoopula memory bubble donkey donkey scoopula
tristan donkey vagina LNB vagina crazy frib Ploopo LNB donkey monkey
discontent scoopula Mission undulate vagina monkey tristan tristan crazy tristan discontent
coelacanth frib vagina Mission tristan coelacanth Ploopo Ploopo tristan monkey culto
Mission Mission monkey Ploopo undulate bubble memory crazy crazy Ploopo frib
LNB monkey tristan memory monkey donkey LNB LNB bubble culto bubble
Ploopo bubble crazy undulate scoopula monkey culto undulate memory Ploopo crazy
frib frib donkey bubble monkey donkey Ploopo vagina scoopula Ploopo vagina
vagina undulate coelacanth frib monkey donkey frib donkey donkey monkey scoopula
Mission Ploopo tristan LNB vagina crazy LNB vagina Mission monkey undulate
scoopula undulate coelacanth scoopula vagina culto scoopula donkey frib frib donkey
LNB LNB crazy undulate crazy tristan tristan tristan memory memory undulate
crazy monkey bubble Ploopo culto crazy vagina coelacanth monkey culto memory
LNB culto LNB Ploopo scoopula coelacanth frib crazy tristan culto memory
tristan memory memory scoopula scoopula memory donkey crazy tristan memory Ploopo
coelacanth Mission bubble tristan coelacanth LNB culto donkey culto Ploopo donkey
discontent vagina undulate tristan monkey coelacanth Ploopo undulate memory donkey vagina
Ploopo Ploopo culto Mission tristan culto Ploopo crazy memory Mission coelacanth
monkey coelacanth Mission culto culto LNB culto discontent culto undulate memory
bubble undulate vagina vagina memory tristan monkey monkey LNB tristan Ploopo
Mission
Spam filtering is one possible application of this type of tool, but the more useful involves taking the mail you *do* want, and sorting it into logical buckets. For instance, let's say work on several open source projects, belong to a couple organizations, and have a real-life job. You could toss a filter in your email that scans each incoming message and throws it in the proper bucket. This allows you to logically separate your mail to reduce confusion of each non-overlapping category.
:-)
Procmail only goes so far, it's really only useful for simple header scanning.. I could really see a good scanner utility being a valuable tool. Maybe Google should share some of their technology..
Josh Woodward
Ploopo memory donkey bubble donkey Mission undulate frib tristan Mission LNB
Ploopo discontent discontent undulate culto coelacanth discontent vagina tristan Mission undulate
LNB vagina memory scoopula monkey donkey bubble donkey culto Mission Ploopo
undulate vagina culto LNB Ploopo tristan LNB discontent scoopula bubble monkey
memory LNB frib crazy coelacanth bubble Mission vagina Mission memory crazy
vagina memory bubble donkey scoopula undulate crazy Mission memory monkey frib
crazy donkey vagina bubble scoopula donkey discontent frib culto undulate tristan
vagina culto bubble crazy scoopula frib memory Mission donkey Ploopo coelacanth
crazy tristan vagina donkey coelacanth culto Mission frib monkey monkey bubble
coelacanth donkey Ploopo monkey coelacanth discontent Mission culto culto frib scoopula
frib bubble scoopula memory vagina donkey vagina crazy Ploopo tristan memory
tristan LNB bubble Ploopo frib culto coelacanth coelacanth monkey vagina Ploopo
scoopula memory Mission monkey Mission bubble culto tristan LNB scoopula donkey
vagina memory Ploopo frib LNB undulate memory donkey frib vagina bubble
Mission discontent coelacanth tristan discontent discontent memory vagina LNB frib culto
Ploopo LNB memory bubble undulate donkey LNB undulate LNB tristan frib
Mission crazy memory Mission culto discontent LNB scoopula memory donkey discontent
frib vagina LNB tristan discontent Ploopo frib tristan bubble Ploopo tristan
discontent vagina donkey frib crazy frib LNB donkey Mission culto LNB
bubble culto coelacanth bubble crazy bubble LNB monkey discontent Mission frib
vagina Ploopo tristan undulate memory crazy monkey undulate Mission Mission monkey
memory LNB Mission undulate frib Ploopo bubble Ploopo bubble memory tristan
scoopula crazy undulate Ploopo scoopula monkey bubble culto crazy monkey memory
coelacanth monkey Mission undulate scoopula crazy vagina coelacanth donkey vagina vagina
discontent tristan Mission Ploopo scoopula Ploopo culto tristan Mission vagina vagina
vagina Mission undulate discontent discontent tristan monkey frib frib frib bubble
Ploopo monkey Mission bubble frib crazy vagina crazy tristan undulate bubble
tristan vagina Ploopo LNB frib vagina frib monkey donkey crazy tristan
frib discontent monkey frib bubble coelacanth vagina bubble crazy memory tristan
crazy donkey memory Ploopo memory undulate undulate bubble scoopula tristan bubble
undulate Mission donkey Ploopo tristan frib monkey frib monkey memory LNB
LNB scoopula frib culto scoopula Mission discontent vagina scoopula Mission donkey
frib tristan Mission donkey culto discontent monkey donkey Mission memory vagina
vagina crazy frib coelacanth memory vagina undulate frib bubble Mission LNB
crazy discontent bubble Ploopo coelacanth crazy Ploopo tristan scoopula vagina Mission
vagina tristan bubble frib monkey donkey Mission tristan Ploopo donkey culto
culto vagina vagina culto Mission vagina culto scoopula undulate Ploopo discontent
undulate LNB Mission monkey monkey frib Ploopo Ploopo discontent undulate culto
Mission crazy crazy tristan frib donkey memory Mission coelacanth monkey vagina
donkey donkey tristan tristan memory bubble discontent bubble Ploopo monkey memory
Ploopo monkey bubble donkey frib coelacanth Ploopo discontent undulate memory Mission
scoopula discontent Ploopo scoopula memory undulate culto Ploopo coelacanth donkey monkey
frib monkey bubble bubble Mission culto scoopula discontent LNB vagina crazy
Ploopo tristan culto monkey vagina bubble vagina Mission discontent bubble vagina
bubble culto tristan frib LNB scoopula LNB donkey vagina Mission Ploopo
vagina coelacanth vagina culto LNB coelacanth donkey culto tristan donkey undulate
monkey culto donkey Mission monkey scoopula memory donkey frib vagina scoopula
coelacanth crazy Mission donkey bubble scoopula monkey scoopula discontent undulate donkey
LNB crazy vagina Mission Mission crazy Ploopo memory frib memory Ploopo
undulate scoopula scoopula culto crazy vagina vagina bubble scoopula culto discontent
LNB monkey bubble crazy undulate donkey crazy frib discontent Mission LNB
undulate LNB donkey culto bubble frib coelacanth tristan LNB tristan monkey
coelacanth coelacanth monkey discontent scoopula LNB vagina frib memory undulate monkey
undulate monkey donkey bubble scoopula culto crazy monkey memory monkey Mission
LNB Mission discontent donkey culto crazy undulate Mission discontent vagina vagina
culto discontent undulate frib LNB monkey frib discontent frib discontent culto
donkey scoopula scoopula frib LNB Mission LNB vagina culto undulate undulate
crazy undulate discontent LNB Mission monkey scoopula tristan coelacanth monkey memory
bubble LNB coelacanth monkey culto frib discontent tristan scoopula donkey frib
Mission discontent donkey LNB culto frib Ploopo culto frib monkey donkey
donkey crazy crazy memory vagina Mission coelacanth discontent donkey memory monkey
monkey undulate undulate memory Mission bubble Mission vagina culto frib monkey
scoopula Ploopo vagina LNB coelacanth monkey coelacanth discontent frib undulate Ploopo
scoopula frib undulate discontent coelacanth bubble LNB frib coelacanth crazy tristan
bubble memory LNB tristan coelacanth LNB scoopula tristan culto undulate memory
scoopula LNB scoopula donkey culto monkey bubble coelacanth LNB LNB tristan
tristan vagina Ploopo Mission donkey vagina vagina monkey discontent frib vagina
scoopula vagina discontent LNB discontent donkey culto Ploopo donkey Ploopo scoopula
monkey discontent vagina donkey coelacanth monkey discontent Ploopo vagina frib Mission
vagina crazy crazy tristan frib undulate culto LNB scoopula tristan scoopula
discontent culto frib crazy tristan tristan culto crazy frib discontent discontent
donkey bubble memory vagina frib bubble crazy Mission memory Mission undulate
tristan culto frib LNB tristan bubble Ploopo tristan coelacanth discontent discontent
monkey Mission crazy Ploopo memory LNB vagina Ploopo tristan culto frib
discontent culto Ploopo tristan Mission LNB coelacanth memory vagina donkey Ploopo
tristan LNB LNB crazy scoopula frib culto monkey Mission memory vagina
LNB LNB scoopula monkey undulate discontent donkey culto scoopula donkey coelacanth
memory undulate Mission bubble undulate memory vagina tristan culto Mission discontent
scoopula Ploopo memory vagina donkey scoopula scoopula tristan frib bubble crazy
coelacanth monkey frib LNB monkey bubble crazy culto vagina tristan crazy
discontent undulate undulate vagina donkey coelacanth tristan undulate scoopula vagina donkey
frib donkey undulate discontent crazy vagina Mission tristan crazy tristan culto
tristan Mission coelacanth memory donkey vagina bubble crazy Mission scoopula Ploopo
monkey discontent frib undulate discontent LNB Ploopo tristan discontent monkey bubble
coelacanth bubble LNB undulate discontent coelacanth LNB memory discontent LNB donkey
culto coelacanth bubble memory crazy undulate vagina frib frib culto bubble
crazy scoopula scoopula LNB frib undulate discontent tristan LNB LNB bubble
coelacanth discontent tristan memory donkey discontent Mission donkey LNB Mission LNB
culto Ploopo Ploopo memory culto monkey Ploopo scoopula memory frib monkey
crazy undulate donkey monkey undulate Mission Ploopo donkey donkey monkey frib
memory memory bubble crazy coelacanth LNB crazy undulate discontent coelacanth scoopula
culto Mission Ploopo Mission vagina monkey coelacanth culto coelacanth scoopula undulate
monkey discontent crazy culto vagina Mission tristan culto vagina monkey LNB
coelacanth undulate tristan memory culto tristan vagina crazy memory undulate culto
coelacanth frib crazy scoopula donkey monkey tristan Ploopo monkey coelacanth vagina
vagina memory memory tristan coelacanth frib tristan tristan scoopula Mission crazy
undulate frib undulate monkey LNB undulate coelacanth scoopula undulate crazy donkey
undulate discontent bubble donkey frib Mission discontent discontent crazy culto frib
Mission memory memory crazy vagina bubble memory donkey discontent Mission Mission
frib memory coelacanth donkey undulate scoopula donkey LNB Ploopo LNB crazy
frib LNB vagina crazy monkey monkey coelacanth undulate discontent tristan Ploopo
Mission LNB coelacanth coelacanth vagina discontent bubble LNB monkey undulate discontent
LNB scoopula monkey culto discontent undulate culto tristan bubble undulate vagina
frib discontent memory Mission tristan frib coelacanth Mission discontent frib monkey
frib monkey frib undulate LNB culto monkey tristan tristan scoopula donkey
undulate donkey frib coelacanth discontent undulate coelacanth Ploopo culto tristan vagina
crazy culto Mission tristan culto monkey frib bubble culto crazy scoopula
LNB crazy monkey donkey donkey memory vagina memory frib discontent discontent
Mission bubble donkey LNB bubble tristan LNB frib Ploopo discontent LNB
undulate Mission frib tristan culto culto scoopula memory bubble donkey scoopula
monkey vagina monkey Mission frib monkey LNB donkey discontent undulate undulate
discontent tristan tristan undulate undulate scoopula bubble bubble scoopula tristan donkey
Mission undulate tristan scoopula vagina scoopula coelacanth frib crazy tristan Mission
tristan coelacanth monkey vagina memory donkey coelacanth donkey Ploopo donkey donkey
crazy monkey monkey frib culto coelacanth Ploopo culto vagina crazy scoopula
tristan crazy monkey coelacanth Ploopo discontent monkey Mission bubble coelacanth frib
coelacanth scoopula scoopula Ploopo Ploopo Ploopo undulate discontent coelacanth LNB donkey
scoopula vagina monkey Ploopo culto crazy tristan Mission undulate monkey vagina
Ploopo donkey scoopula undulate vagina Mission frib coelacanth vagina vagina memory
monkey culto frib culto memory undulate crazy scoopula discontent donkey tristan
culto vagina crazy monkey bubble culto coelacanth donkey tristan donkey bubble
vagina tristan tristan donkey bubble discontent coelacanth frib tristan discontent coelacanth
discontent tristan undulate coelacanth undulate monkey Ploopo scoopula memory discontent vagina
LNB Mission memory donkey coelacanth memory crazy frib culto tristan frib
vagina coelacanth donkey monkey Ploopo LNB frib Mission memory scoopula coelacanth
frib crazy LNB bubble donkey monkey donkey discontent frib bubble frib
frib frib tristan undulate coelacanth tristan discontent discontent scoopula Mission coelacanth
vagina bubble LNB tristan Mission crazy vagina bubble scoopula undulate coelacanth
vagina frib bubble culto Ploopo vagina undulate Ploopo monkey donkey crazy
Ploopo bubble Mission scoopula memory memory culto discontent Ploopo donkey bubble
vagina LNB Ploopo Ploopo bubble bubble tristan discontent frib monkey vagina
frib scoopula LNB vagina coelacanth crazy frib LNB undulate donkey Mission
crazy undulate crazy Ploopo bubble discontent LNB LNB LNB crazy memory
scoopula scoopula LNB LNB Ploopo coelacanth discontent Ploopo Mission tristan donkey
tristan memory LNB bubble monkey culto discontent Ploopo bubble tristan vagina
frib bubble frib frib LNB Ploopo coelacanth crazy crazy bubble coelacanth
tristan bubble coelacanth frib donkey undulate crazy crazy coelacanth tristan culto
Ploopo donkey crazy Mission crazy culto memory frib undulate frib undulate
crazy bubble culto monkey Ploopo tristan monkey undulate scoopula discontent Ploopo
scoopula culto Mission discontent discontent Mission LNB crazy scoopula bubble donkey
monkey tristan crazy monkey vagina culto scoopula culto culto bubble crazy
vagina discontent donkey bubble monkey monkey Mission scoopula Ploopo undulate crazy
crazy Ploopo bubble donkey coelacanth Mission tristan Ploopo discontent monkey bubble
tristan frib donkey donkey monkey Mission memory crazy donkey undulate crazy
tristan donkey monkey Mission Ploopo Mission crazy coelacanth scoopula donkey culto
discontent frib frib culto crazy discontent Ploopo LNB frib crazy Ploopo
LNB bubble bubble culto LNB coelacanth memory tristan tristan vagina crazy
LNB memory LNB Mission donkey culto culto frib coelacanth donkey donkey
monkey tristan undulate LNB undulate Mission memory bubble monkey scoopula scoopula Ploopo memory donkey bubble donkey Mission undulate frib tristan Mission LNB
Ploopo discontent discontent undulate culto coelacanth discontent vagina tristan Mission undulate
LNB vagina memory scoopula monkey donkey bubble donkey culto Mission Ploopo
undulate vagina culto LNB Ploopo tristan LNB discontent scoopula bubble monkey
memory LNB frib crazy coelacanth bubble Mission vagina Mission memory crazy
vagina memory bubble donkey scoopula undulate crazy Mission memory monkey frib
crazy donkey vagina bubble scoopula donkey discontent frib culto undulate tristan
vagina culto bubble crazy scoopula frib memory Mission donkey Ploopo coelacanth
crazy tristan vagina donkey coelacanth culto Mission frib monkey monkey bubble
coelacanth donkey Ploopo monkey coelacanth discontent Mission culto culto frib scoopula
frib bubble scoopula memory vagina donkey vagina crazy Ploopo tristan memory
tristan LNB bubble Ploopo frib culto coelacanth coelacanth monkey vagina Ploopo
scoopula memory Mission monkey Mission bubble culto tristan LNB scoopula donkey
vagina memory Ploopo frib LNB undulate memory donkey frib vagina bubble
Mission discontent coelacanth tristan discontent discontent memory vagina LNB frib culto
Ploopo LNB memory bubble undulate donkey LNB undulate LNB tristan frib
Mission crazy memory Mission culto discontent LNB scoopula memory donkey discontent
frib vagina LNB tristan discontent Ploopo frib tristan bubble Ploopo tristan
discontent vagina donkey frib crazy frib LNB donkey Mission culto LNB
bubble culto coelacanth bubble crazy bubble LNB monkey discontent Mission frib
vagina Ploopo tristan undulate memory crazy monkey undulate Mission Mission monkey
memory LNB Mission undulate frib Ploopo bubble Ploopo bubble memory tristan
scoopula crazy undulate Ploopo scoopula monkey bubble culto crazy monkey memory
coelacanth monkey Mission undulate scoopula crazy vagina coelacanth donkey vagina vagina
discontent tristan Mission Ploopo scoopula Ploopo culto tristan Mission vagina vagina
vagina Mission undulate discontent discontent tristan monkey frib frib frib bubble
Ploopo monkey Mission bubble frib crazy vagina crazy tristan undulate bubble
tristan vagina Ploopo LNB frib vagina frib monkey donkey crazy tristan
frib discontent monkey frib bubble coelacanth vagina bubble crazy memory tristan
crazy donkey memory Ploopo memory undulate undulate bubble scoopula tristan bubble
undulate Mission donkey Ploopo tristan frib monkey frib monkey memory LNB
LNB scoopula frib culto scoopula Mission discontent vagina scoopula Mission donkey
frib tristan Mission donkey culto discontent monkey donkey Mission memory vagina
vagina crazy frib coelacanth memory vagina undulate frib bubble Mission LNB
crazy discontent bubble Ploopo coelacanth crazy Ploopo tristan scoopula vagina Mission
vagina tristan bubble frib monkey donkey Mission tristan Ploopo donkey culto
culto vagina vagina culto Mission vagina culto scoopula undulate Ploopo discontent
undulate LNB Mission monkey monkey frib Ploopo Ploopo discontent undulate culto
Mission crazy crazy tristan frib donkey memory Mission coelacanth monkey vagina
donkey donkey tristan tristan memory bubble discontent bubble Ploopo monkey memory
Ploopo monkey bubble donkey frib coelacanth Ploopo discontent undulate memory Mission
scoopula discontent Ploopo scoopula memory undulate culto Ploopo coelacanth donkey monkey
frib monkey bubble bubble Mission culto scoopula discontent LNB vagina crazy
Ploopo tristan culto monkey vagina bubble vagina Mission discontent bubble vagina
bubble culto tristan frib LNB scoopula LNB donkey vagina Mission Ploopo
vagina coelacanth vagina culto LNB coelacanth donkey culto tristan donkey undulate
monkey culto donkey Mission monkey scoopula memory donkey frib vagina scoopula
coelacanth crazy Mission donkey bubble scoopula monkey scoopula discontent undulate donkey
LNB crazy vagina Mission Mission crazy Ploopo memory frib memory Ploopo
undulate scoopula scoopula culto crazy vagina vagina bubble scoopula culto discontent
LNB monkey bubble crazy undulate donkey crazy frib discontent Mission LNB
undulate LNB donkey culto bubble frib coelacanth tristan LNB tristan monkey
coelacanth coelacanth monkey discontent scoopula LNB vagina frib memory undulate monkey
undulate monkey donkey bubble scoopula culto crazy monkey memory monkey Mission
LNB Mission discontent donkey culto crazy undulate Mission discontent vagina vagina
culto discontent undulate frib LNB monkey frib discontent frib discontent culto
donkey scoopula scoopula frib LNB Mission LNB vagina culto undulate undulate
crazy undulate discontent LNB Mission monkey scoopula tristan coelacanth monkey memory
bubble LNB coelacanth monkey culto frib discontent tristan scoopula donkey frib
Mission discontent donkey LNB culto frib Ploopo culto frib monkey donkey
donkey crazy crazy memory vagina Mission coelacanth discontent donkey memory monkey
monkey undulate undulate memory Mission bubble Mission vagina culto frib monkey
scoopula Ploopo vagina LNB coelacanth monkey coelacanth discontent frib undulate Ploopo
scoopula frib undulate discontent coelacanth bubble LNB frib coelacanth crazy tristan
bubble memory LNB tristan coelacanth LNB scoopula tristan culto undulate memory
scoopula LNB scoopula donkey culto monkey bubble coelacanth LNB LNB tristan
tristan vagina Ploopo Mission donkey vagina vagina monkey discontent frib vagina
scoopula vagina discontent LNB discontent donkey culto Ploopo donkey Ploopo scoopula
monkey discontent vagina donkey coelacanth monkey discontent Ploopo vagina frib Mission
vagina crazy crazy tristan frib undulate culto LNB scoopula tristan scoopula
discontent culto frib crazy tristan tristan culto crazy frib discontent discontent
donkey bubble memory vagina frib bubble crazy Mission memory Mission undulate
tristan culto frib LNB tristan bubble Ploopo tristan coelacanth discontent discontent
monkey Mission crazy Ploopo memory LNB vagina Ploopo tristan culto frib
discontent culto Ploopo tristan Mission LNB coelacanth memory vagina donkey Ploopo
tristan LNB LNB crazy scoopula frib culto monkey Mission memory vagina
LNB LNB scoopula monkey undulate discontent donkey culto scoopula donkey coelacanth
memory undulate Mission bubble undulate memory vagina tristan culto Mission discontent
scoopula Ploopo memory vagina donkey scoopula scoopula tristan frib bubble crazy
coelacanth monkey frib LNB monkey bubble crazy culto vagina tristan crazy
discontent undulate undulate vagina donkey coelacanth tristan undulate scoopula vagina donkey
frib donkey undulate discontent crazy vagina Mission tristan crazy tristan culto
tristan Mission coelacanth memory donkey vagina bubble crazy Mission scoopula Ploopo
monkey discontent frib undulate discontent LNB Ploopo tristan discontent monkey bubble
coelacanth bubble LNB undulate discontent coelacanth LNB memory discontent LNB donkey
culto coelacanth bubble memory crazy undulate vagina frib frib culto bubble
crazy scoopula scoopula LNB frib undulate discontent tristan LNB LNB bubble
coelacanth discontent tristan memory donkey discontent Mission donkey LNB Mission LNB
culto Ploopo Ploopo memory culto monkey Ploopo scoopula memory frib monkey
crazy undulate donkey monkey undulate Mission Ploopo donkey donkey monkey frib
memory memory bubble crazy coelacanth LNB crazy undulate discontent coelacanth scoopula
culto Mission Ploopo Mission vagina monkey coelacanth culto coelacanth scoopula undulate
monkey discontent crazy culto vagina Mission tristan culto vagina monkey LNB
coelacanth undulate tristan memory culto tristan vagina crazy memory undulate culto
coelacanth frib crazy scoopula donkey monkey tristan Ploopo monkey coelacanth vagina
vagina memory memory tristan coelacanth frib tristan tristan scoopula Mission crazy
undulate frib undulate monkey LNB undulate coelacanth scoopula undulate crazy donkey
undulate discontent bubble donkey frib Mission discontent discontent crazy culto frib
Mission memory memory crazy vagina bubble memory donkey discontent Mission Mission
frib memory coelacanth donkey undulate scoopula donkey LNB Ploopo LNB crazy
frib LNB vagina crazy monkey monkey coelacanth undulate discontent tristan Ploopo
Mission LNB coelacanth coelacanth vagina discontent bubble LNB monkey undulate discontent
LNB scoopula monkey culto discontent undulate culto tristan bubble undulate vagina
frib discontent memory Mission tristan frib coelacanth Mission discontent frib monkey
frib monkey frib undulate LNB culto monkey tristan tristan scoopula donkey
undulate donkey frib coelacanth discontent undulate coelacanth Ploopo culto tristan vagina
crazy culto Mission tristan culto monkey frib bubble culto crazy scoopula
LNB crazy monkey donkey donkey memory vagina memory frib discontent discontent
Mission bubble donkey LNB bubble tristan LNB frib Ploopo discontent LNB
undulate Mission frib tristan culto culto scoopula memory bubble donkey scoopula
monkey vagina monkey Mission frib monkey LNB donkey discontent undulate undulate
discontent tristan tristan undulate undulate scoopula bubble bubble scoopula tristan donkey
Mission undulate tristan scoopula vagina scoopula coelacanth frib crazy tristan Mission
tristan coelacanth monkey vagina memory donkey coelacanth donkey Ploopo donkey donkey
crazy monkey monkey frib culto coelacanth Ploopo culto vagina crazy scoopula
tristan crazy monkey coelacanth Ploopo discontent monkey Mission bubble coelacanth frib
coelacanth scoopula scoopula Ploopo Ploopo Ploopo undulate discontent coelacanth LNB donkey
scoopula vagina monkey Ploopo culto crazy tristan Mission undulate monkey vagina
Ploopo donkey scoopula undulate vagina Mission frib coelacanth vagina vagina memory
monkey culto frib culto memory undulate crazy scoopula discontent donkey tristan
culto vagina crazy monkey bubble culto coelacanth donkey tristan donkey bubble
vagina tristan tristan donkey bubble discontent coelacanth frib tristan discontent coelacanth
discontent tristan undulate coelacanth undulate monkey Ploopo scoopula memory discontent vagina
LNB Mission memory donkey coelacanth memory crazy frib culto tristan frib
vagina coelacanth donkey monkey Ploopo LNB frib Mission memory scoopula coelacanth
frib crazy LNB bubble donkey monkey donkey discontent frib bubble frib
frib frib tristan undulate coelacanth tristan discontent discontent scoopula Mission coelacanth
vagina bubble LNB tristan Mission crazy vagina bubble scoopula undulate coelacanth
vagina frib bubble culto Ploopo vagina undulate Ploopo monkey donkey crazy
Ploopo bubble Mission scoopula memory memory culto discontent Ploopo donkey bubble
vagina LNB Ploopo Ploopo bubble bubble tristan discontent frib monkey vagina
frib scoopula LNB vagina coelacanth crazy frib LNB undulate donkey Mission
crazy undulate crazy Ploopo bubble discontent LNB LNB LNB crazy memory
scoopula scoopula LNB LNB Ploopo coelacanth discontent Ploopo Mission tristan donkey
tristan memory LNB bubble monkey culto discontent Ploopo bubble tristan vagina
frib bubble frib frib LNB Ploopo coelacanth crazy crazy bubble coelacanth
tristan bubble coelacanth frib donkey undulate crazy crazy coelacanth tristan culto
Ploopo donkey crazy Mission crazy culto memory frib undulate frib undulate
crazy bubble culto monkey Ploopo tristan monkey undulate scoopula discontent Ploopo
scoopula culto Mission discontent discontent Mission LNB crazy scoopula bubble donkey
monkey tristan crazy monkey vagina culto scoopula culto culto bubble crazy
vagina discontent donkey bubble monkey monkey Mission scoopula Ploopo undulate crazy
crazy Ploopo bubble donkey coelacanth Mission tristan Ploopo discontent monkey bubble
tristan frib donkey donkey monkey Mission memory crazy donkey undulate crazy
tristan donkey monkey Mission Ploopo Mission crazy coelacanth scoopula donkey culto
discontent frib frib culto crazy discontent Ploopo LNB frib crazy Ploopo
LNB bubble bubble culto LNB coelacanth memory tristan tristan vagina crazy
LNB memory LNB Mission donkey culto culto frib coelacanth donkey donkey
monkey tristan undulate LNB undulate Mission memory bubble monkey scoopula scoopula
bubble
bubble
Why are there so many people complaining about a PS link? The answer is simple: ./ is news for nerds, not for geeks.
So while the average geek keeps his favorite postscript viewer handy, the standart nerd wonders about such an ancient format and does not know how to feed his acrobat viewer with it...
Here is the solution for those irritated ones: try this piece of ancient software on the ancient adobe format, and you can miracously view it's contents!
Have fun and keep your google handy!
I get alot of spam mail still... I was wondering if Hotmail could ever creat MD5 sums of every e-mail and keep a database, then create some kind of popularity grid where you could, for instance, say hey i don't want e-mail that everyone else is getting...
*shrug* maybe it'd work, maybe not... i'm just tired of getting spam..
I have enjoyed using the VM module for Emacs. It allows sorting your entire Inbox into separate categorized mail boxes via regular expressions. Basically with one shift-A keystroke, my entire day's worth of mailing list stuff gets whisked away into a half-dozen different files. After this, I feel really sorry for people trapped in the Outlook dungeons!
Healthcare article at Kuro5hin
For those without postscript readers, a PDF version is available here.
I'd just like a way to reorganize the emails without affecting them, so that it acts more or less like a database report allowing me to group based on different criteria. For example, if I normally manually organize my emails into separate folders by Topic:Region (where each topic is arising), I'd like to be able to reorganize them by Region:Topic for a different perspective (what's going on in each region).
Check out Enfish Onespace for those of you running MS Outlook. Not only does it do great text mining of all e-mails, it does the same with contacts and with files on your hard drive (the professional version handles network files, as well).
:)
It's got a clean UI, but it is a bit hard getting used to. I've found it to be a great tool for finding info in a snap - I just enter a search phrase and instantly get a list of relevant e-mails, Word docs, spreadsheets, contacts, and even websites.
And nope, I'm not associated with them in any way - I just like the product.
--
Welcome to the land of the easily amused...
I also use this technique for my externally hosted domain...I get all the mail addressed to any user in the domain, but its easy to set up mail client filters to remove those with are addressed To:, say, potentialspammer1@mydomain.
So, if there's any possibility of SPAM, I just invent a new user. Unfortunately, I didn't figure this out quite soon enough and I have some users which get spam and real mail, which I can't afford to filter to trash - people buying their own domains (come on, its like $15 a year) should be thinking ahead.
Also, its not as neat a set up as having my own POP server bounce back the message (which might mean you get off the spam list one day!). More importantly, filtering the To: field, doesn't help me most times, since spammers set the To: to "READTHIS" and use Bcc: for their spammies (is that a word!).
ALSO
Here's an unrelated question for anyone else who owns a domain like me, where they get a catch all POP box.
How do you guys make sure people USE your nice domain name?
In other words, its okay having a POP box, mail.mydomain.com, but you never seem to get offered the services of an SMTP server through which you can send your messages From: this nice address.
I would hazard that most people rely on Reply-To:, which is all very well, except that not all mail clients respect it, and you may want to entirely obscure the actual From:.
Of course, mail clients like Emacs and Mozilla make it easy to arbitrarily set your From:, however you then have to get this through whatever SMTP server you have available (and in order to block spammers and other pranksters, you will increasingly find that most will only send mail if the From: agrees with your user name).
One of the reasons I moved to linux was so I could run sendmail and not rely on other peoples SMTP servers. The is okay at work, since we have direct internet access, but from home when I dial up, it doesn't work.
I don't think my ISP likes to have people sending mail from their own computers, I get name resolution errors from sendmail when attempting to send email (but have no problem with DNS for web), so I think that perhaps the ISPs DNS servers refuse to give up MX records.
Anyone else in a similar boat?
Just use GhostView...
I've often thought it would be great if I could save my email to a mysql (or postgres, if you prefer) that would automatically parse the header and body into table fields. Then when you want to search it you can use SQL queries instead of the covoluted grep commands I use now.
Doesn't seem hard to write. Anybody know of such a thing?
"Perhaps even one of them Perl monkeys will quickly hack such a background tool."
Been done already. Check out Mail::Miner.
Matt. Want XML + Apache + Stylesheets? Get AxKit.
Have you seen that http://homepage.mac.com/zoe_info/
My reaction was to want an e-mail reading program that didn't require any filter configuration, though I imagined it would do well to be given a few hints, such as who my boss is, who my mother is, and who my wife is. Other than that, let the program figure it out.
Imagine the canonical, old-fashioned secretary temp. She ('cause that's what the canonical version was) didn't have to know anything domain-specific to sort the morning mail. Magazines go together, bills go together, personal letters go together, etc.
I imagine an automated version for my e-mail. Look at who it is "to" (am I on the list?), look at who is "cc"-ed (am I on that list?), look at who it is from (my boss, wife, or mother?), look at who else it is to (boss, wife, or mother?), look at the thread it is part of (is it responding to something I previously wrote?), look at the content (does it mention me, things I have written, my boss, wife, or mother?). Was it sent to a mailing list? Was it written by someone I have explicitly written to (once or many times?)? Was it written by someone who has previously sent me direct e-mail (once or many times?)? Those ideas are just the obvious ones, think of others. Think of more. (Does it talk about sex, credit card merchant accounts, stock tips, or Nigerian money?)
Now take that and sort it by importance and similarity. Look for a way to present me in a descriptive summary, arranged in a hierarchy with a top-level of, say, 3 to 9 categories, a greatest depth no greater than, say, 4, and keep the sub-branching at intermediate nodes between 3 and 5--but don't max out all those dimensions at once, try to keep the total number of leaf categories to under, say, two dozen. Try to make more important items land higher in the tree and with few siblings, grouped with siblings of similar importance. (Maybe give an importance weight to each e-mail and balance the tree on that scale, that would float e-mails to me from my boss about my mother and wife really high with few siblings.)
This summary needs to be integrated with a complete index of the e-mail so I can see how a message fits into a larger thread, how it fits into previous e-mails.
I (the user) would need to tell the program when to make me a summary of my e-mail (e-mail reading is different when a lot comes in or just a little), and I want to be able to browse through old summaries, including deciding to see composite summaries or, say, the last several days, a week (or three), month, year, or 400 days.
So I think it ends up being a 4-part user interface:
List of summaries (which can be manipulated).
A given summary.
Exhaustive thread/date/subject/sender list (analogous to what every e-mail reader seems to have now). Note that this view could effectively be turned into an exhaustive address book. Frequent (favored) correspondents could be highlighted by me for ease in sending a new e-mail, and also to provide importance hints to the program. This is where I might say who my boss/wife/mother is.
A body of a (or more) specific e-mail being read, written, or old e-mail (sent or received) being reviewed.
And I could go on, but I won't. If anyone wants to write such a thing and wants to hear more, send me an, um, e-mail.
-kb, the Kent who has been saving all his e-mail (including spam!) for a year or so, providing plenty of raw material to test any such program.
Please check out:
http://homepage.mac.com/zoe_info/
Zoe is way ahead of this curve.
Phorecast downloads all your email into a database of your choosing; it is database abstracted using PHP's PEAR DB library.
.tsv translation file for any language you like. Version 0.5 (on the way) improves these functions, and adds a todo list as well.
Phorecast is a web application written in PHP that combines email, calendar, and address book functions. It is language abstracted, so you can write a
Full disclosure: I wrote it, and I use it as my primary email client.
Try out Phorecast, open-source email, calendar,
Really, the diagrams help convey many of the points, but do the equations really tell you anything? Can anyone actually read those and explain them?
If I didn't know better, I'd think these sorts of papers ( which are common ) were a cheap attempt to sneak obvious claims past the patent office. I guess it's this sort stuff that got the patent office in the trouble it has seen.
How about converting to html?
This may also be a reverse DNS resolution problem. Check that your IP resolves to your hostname and that your hostname resolves to your IP. If not, some sendmail installations will reject your mail. Also, make sure your sendmail is sending out the correct hostname - eg, you can set up your machine so that it thinks its hostname is something.domain.com instead of some-long-crap-dsl-023-094.domain.com where something.domain.com is not an actual DNS record. This works fine for everything except when sendmail starts sending out emails claiming something.domain.com as originator.
Another thing you can do is configure sendmail to send all mail addressed to "user+any_arbitrary_string@domain.com" to "user@domain.com". This is useful since I don't have to do anything to generate a new email address. Search google.
I'll add that giving out a separate email addy for every company works beautifully. It also lets you know when some company sells your email address, something they will never admit to doing otherwise. I now get zero spam in my inbox.
The main result in Kleinberg's paper relates to finding NEW topics that start to appear in the stream. Let's say you already have categorization filters (procmail, keyword filters, your own set of folder hierarchies, whatever...), but there's a new topic that starts showing up in your mail, or in your newsgroup feed, or on CNN. Klienberg's result is a way to find that the new stuff really is NEW, and you might want to group it up together, and make a folder for it. You could do that automatically, or by hand, but first you have to know that there's a topic.
there's a bunch of other work in this area, what the NLP types call TDT -- "Topic Detection and Tracking"
Check out sneakemail.com - it does basically this, but at their domain name, and you can set filters of particular addresses, or just delete them. Very useful idea, I'd definitely be willing to pay for it though...
jzw of Mozilla/Netscape fame have a hypothetical program called Intertwingle which is (Score:5,Interesting) ....
RFC1925
There's been lots of work on auto-classifying email. I did my semester project in Machine Learning on this in 1999. It's a fairly simple study, but it seems like a Naive Bayesian classifier using word counts as features does a pretty decent job of classifying email, and does really well on spam.
The paper is here here.
J.
who the hell gets so much email they need to
mine for text, christ ??!! dont change your email filtering, change your pathetic life !!
there are plenty of other things far more worth mining than TEXT
As much as slashdotters hate lawyers...
And most politicians...
Maybe we should learn how to use them...
Use the laws in place. Sue them for the costs associated with spam. Sue them when they break the laws that exist to protect consumers. Whether it is spam, telemarketers, or Best Buys. Stiff it to them. Out smart them. After all, arent we geeks and nerds? By the world's definition arent we all supposed to be smarter, or a step above average person?
----- LoboSoft specializes in Digital Language Lab
Here
/cj
www.80-20.com (I think)
Integrates with Outlook (not UNIX version). But it offers real-time indexing of email, contacts, local and networked files. Super cheap for what you get.
It's saved my butt a hundred times when I can only remeber a fragment of someone's contact info, message or whatever.
They're the worst marketers in the world. They owe me for this one!
http://www.hiredinsight.com
i'm taking a class with kleinberg right now and he's a great lecturer. if anyone is interested in algorithms of any kind, go read his papers.
Aha, is this why it works at work (where my hostname is correct and resolvable), but not at home with my ISP, where my hostname remains the same but could not be looked up?
I just dial of over a modem, and its possible I configured that kind of perculiarly, because of wanting to switch between the LAN at work and my dialup at home.
There are plenty of e-mail mining tools in development. This particular work takes one particular approach to mining the data. Whether this approach will turn out to be useful remains to be seen.
I also have my own domain name but I'm limited to 5 forwarded email addresses. I wanted to do what you suggested a while ago but couldn't. Then I stumbled across Sneakemail and it basically did everything I had intended anyway.
In a nutshell, you sign up for an account, giving only a contact email address (I use spam AT threewordslong DOTTY com). Once logged in you can create a new, randomized email address for each new web service that needs an email address. If one of these services spams or sells your sneakemail address you: a) know exactly who did it and cease further business with them and b) can filter on that specific email address.
It's a great service and no, I don't work for them...
"Where is the wisdom we have lost in knowledge, and where is the knowledge we have lost in information?"-T.S.Eliot
There are several articles on /. concerning lawsuits against spammers.
i ng &op=stories&author=&topic=111§ion=&sort=1
http://slashdot.org/search.pl?query=sue+sued+su
A fool throws a stone into a well and a thousand sages can not remove it.
The rogue marketers will just let another company entity send th enext spam.
Ie. starta a new throw-away company each time they want to spam us.
Qmail is good for this sort of thing. By default, a user receives everything at username-*@domain.com.
.qmail-amazon and .qmail-slashdot files in your home directory and have a .qmail catch-all.
So, I subscribe to amazon with username-amazon@domain.com, slashdot with username-slashdot@domain.com etc.
You can then control the delivery location of mails to these recipients using
This comes in handy for filing mailing-lists away, filtering out spam etc. Its also interesting to see who's sold you down the river to spammers, I recently started receiving spam to username-bsdtoday@domain.com... bastards!
Cheers,
Si
I could list it all here, but it's much more efficient to just point people at:
http://www.iarchitect.com/lotus.htm
(Which is a site that everyone should read before doing UI stuff.)
Sample of one of the "best" bits:
Judging from the number of visitors who have mentioned it, the process of copying messages in Notes is perhaps its worst interface "feature". Apparently, when mail messages are copied from one folder to another, the message itself is not copied; Notes creates a "reference" to the message. Unbeknownst to the user, if you delete the reference, Notes will in turn delete the message itself. Similarly, deleting the message will cause all references to it to also be deleted.
I'd like to find something like this - where
as I browse across a web page I could active
a program that would look at the page, and suggest a series of folders that appear to be relevant.
If I agree, I click okay and go on. If I think a category is unnecessary, or missing, I would
have the option of adding a category.
I see this as a parallel need to the mining
of the email.
URL: http://xanga.com/lvirden > Quote: Saving the world before bedtime. Even if explicitly stated to the contrary, n
SWISH++ (my search engine) specifically knows to index mail/news files (including text, HTML, RTF, LaTeX files) and attachments of any of those (in quoted-printable or base64 encodings). It can also index any other kind of attachment via external filter programs. A procmail recipe for auto-splitting incoming mail is included in the distro. I also believe that my statement of SWISH++ being the fastest open-source indexer is accurate.
If you reply, do so only to what I explicitly wrote. If I didn't write it, don't assume or infer it.
SpamBouncer is a set of procmail recipes to filter spam.