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Working Bayesian Mail Filter
zonker writes "A real, working honest to god Bayesian spam filter. I've been waiting for something like this for a while (since I first read Paul Graham's research paper on this very topic a few weeks ago). Well here's POPFile, a small but extremely effective Perl script that runs on just about any system Perl does. After just a little training was I able to get very effective filtering out of it. From what I understand the new email client that comes with OS X Jaguar has a feature similar to this, but I don't know if it is true Bayesian. Hopefully this kind of feature will become more prevalant in client software as I see the Google results for it are growing."
Would anyone care to explain what is a "Bayesian" mail filter?
Saw this a few weeks back... Spam filter in Python using Naive Bayes.
And I'm going to check it out right now :) But one long standing I fear with such solutions is spammer's adapting to new environments (changing wording used, making the emails look more professional). Sure, they're dumb shits but they're still humans with brains.
Any server-side solutions (MTA==qmail, MDA==procmail) using this (Naive-Bayesian) technique out there?
The mozilla mail client is getting a Bayesian mail filter, too. See http://bugzilla.mozilla.org/show_bug.cgi?id=163188 . Unfortunately, it probably won't show up until after version 1.2 is released.
Try searching for "bayesian email filter" instead of just "bayes email filter" (as in the news post). You'll get better results and more hits since Google doesn't match "*bayes*" (as one would think) when searching for "bayes", but only the actual word "bayes".
Beware: In C++, your friends can see your privates!
More intelligent classification algorithms can solve non-linear problems far better. Check out Kernel Machines and, somewhat older, Maximum Entropy models.
Enough nerd talk for today :-)
We need the Stalin Mail Filter (TM) -- it detects spam, hunts down the spammer, and exiles them to Siberia.
evil adrian
Sure it's great that someone made one, but its a perl script. We might be able to use perl , but most of the "normal" people have never even heard of perl, let alone them having knowledge of running perl scripts. It would be great if someone ported this, to an .exe file or something that everyone could run. It'll probably happen eventually.
Can someone explain why this filter would be useful to me?
"The lesson to be learned is not to take the comments on slashdot too literally." --Vinnie Falco, BearShare
This isn't exactly the first bayesian mail filter out there. I've been using ESR's bogofilter for weeks now, and I must say it works better than I could have ever imagined. Bogofilter however is simply for sorting out spam, while it appears this filter can sort out other things. But honestly, I can setup some simple filters to separate personal emails from work emails, so I'm not entirely sure the extra stuff is that useful.
-Stype
Bus error -- driver executed.
Does anyone know of any spam solutions for IMAP? Everything I've seen out there is POP3, but goddammit I like my IMAP folders!!! (Not to mention that the server on which my e-mail resides gets backed up nightly...)
evil adrian
You know, on this issue, you really depress me. You are clearly not of the academic nature, so your stance toward something thats probably way above your head really frustrates part of me.
As long as you're not developing the idea, it shouldnt matter how it works as long as it works.
I read the original article here as you did to. After all the mumbo jumbo about learning, i picked out one effective tip from the article on filtering my email: filter out HTML.
With 1 line of regex I eliminate 95% of my spam:
match and throw it out.
-- -- --
Help my mini cause: My journal
What will make this thing work is if it is integrated with the e-mail client.
With this tool, you unfortunately have to manually add a message of a certain classification (work, pr0n, spam, family...) to the progrma through the perl script -- very awkward.
A tool like this need to run as a daemon and 'notice' when a message is added to a folder. Unfortunately, with different formats for e-mail folders, it's a much tougher job.
As it stands, with something like Outlook, I'd have to export each message individually, then run the Perl script. I can probably add a macro to do that (with its own pains -- you add a VBA macro to Outlook and it gripes every time you start up), and possibly even one that responds to filing in a folder.... hmm... maybe I will try this out.
Design for Use, not Construction!
I work on the helpdesk of a small ISP; I also take care of the spam filtering, and answer abuse@. We recently added SpamAssassin, and God does it rock. (The big spike you see is me getting MRTG to graph what SA catches now; it's 6-10 times better than what we used to catch.)
But I still get complaints from our customers about spam that gets through. Just the other day a crapload got through because it was relatively subdued spam (no webbugs, NO LINE OF YELLING, etc); unfortunately, it also advertised pictures of young boys having sex. It's hard to explain why it's very, very hard to filter for this sort of thing, especially when I'm going through the talk for the nth time this week. (I need a good analogy that non-geeks can understand; I'm still looking.)
The good folks at DeerSoft have a version of SpamAssassin for Outlook, and are promising one for OE Real Soon Now. But I would loooooooooooooooooooooooove a good spam program -- this or SA or something else -- that I could point our customers to. Download, double-click, say yes, and bam it's installed. I can figure out how to install this on a Unix box; I could probably, eventually figure out how to do it on a Windows box; there's no way the customers could do it.
Or am I missing good, free spam filtering for Windows? Can anyone point me in the right direction?
Slightly OT: There has got to be a huge market for setting up spam filtering for small businesses. My idea: Tell 'em that if they provide the box -- an old Pentium or 486 will do -- I'll set up spam filtering and a firewall on it, set up some maintenance tools (whitelist this, firewall that). They get great mail service, I get $x00.
Carousel is a lie!
That's /. for you. You guys have modded up to 5 a post that is wrong in both of the equations it posts.
It should be:
Pr(h|D) = Pr(D|h) * Pr(h) / Pr(D)
and:
Pr("SPAM"|Email) = Pr(Email|"SPAM") * (proportion of spam) / (probability of getting this paticular Email)
jabber: johnynek@jabber.org
I think you have failed to understand how the filter works.
It is "trained" on a corpus of spam, which is compared to a corpus of known good messages. The important part is that YOU, the user, supply the spam corpus and the good messages. Thus in your case, as long as your "good spamlike messages" are in your "known good pile", similar new ones from the same source will not be tagged as spam. This is where the statistical approach shines over simple keyword matching.
Go on, read about how it works. You might learn something.
SquirrelMail is a WebMail client implemented in PHP. I use the client, but not the plugin (I use Razor).
Well, if all spam is indistinguishable from the legitimate spamlike messages you want to see, then no filter will help you.
However, it seems more likely that a large proportion of spam is distinguishable from mail you want to see. It's quite plausible that you don't want to see messages about nympho sluts, or penis enlargement, or breast enlargement (or at least not all three), and that a naive Bayesian filter could easily distinguish these and other spams from mail you do want to see.
Bogofilter has been out since august, and does this bayesian spam-stuff in C, which probably will run a bit faster than the perl or python versions just because of it's compiled-ness. I've never run it myself, but people on debian lists say it works better or not as good as spamassassin.
You can't see this if you have sigs turned off.
This may be self-regulating. Consider the Skinner box; if something is capable of perfectly emulating recognition of Chinese, then it can be said to recognize Chinese. Likewise, if a spammer becomes sufficiently skilled at writing undetectable prose, he or she will have reached a skill level at which he or she can pursue more profitable writing ventures. The margins in spam are pretty small. Those spams are being written by morons because morons are cheap.
Stop-Prism.org: Opt Out of Surveillance
Great, now the spammers will hire mathematicians to figure out how to best defeat the common algorithms used to calculate Pr(D|h). It is the same old story. In a war over information only the mathematicians win.
Give a hand, not a hand-out.
but, unlike your secretary not showing you things. you can just set up the filter to put the spam in a spam folder. you can then periodically look at it and see if there are any false positives. or you can tell the filter to delete things that are 95% spam, but put things that are still most likely spam in a special folder. that's what's great about learning algorithims, they can always adapt to what you want (if you teach them enough).
I just received the November edition of the TPJ which included a fine article "perlcc & Compiling Perl Script".
In short, the filter script could be compiled to C and built to a native binary for a variety of platforms eliminating the need for a Perl interperter.
One of my pet peeves is the obsession that folks have with zeros. An example is the year 2000. In base 10 you get beaucoup zeros whereas with hex you get 7D0, or 11A6 (base 12), or 3720 (octal), or 11111010000 (binary). Zeros are an artifice of both the base, and numeral system used to represent a pure number. Thus, the fact that most humans use the decimal Indo-Arabic numeral system to represent it is the only reason for all those zeros. Use another base, or numeral system to represent 2000, you don't get beaucoup zeros.
The real properties of pure numbers are the relationships that they have with other numbers, and not the symbology used to represent them.
"Oh drat these computers, they're so naughty and so complex, I could pinch them." --Marvin the Martian
An advertised false positive rate of 0% is nice, but why not additional research into the spam, to attempt to categorize into blatant spam, probable spam, borderline, and non-spam, and see if false positives can be plopped into the borderline categories.
Also, from what I saw in the article, there will already be a next level that spam can take: image-based messages, misspellings of key words (klik, Clic, Clik, etc), using 0xfe0000 for almost-bright-red.
Hey, I'm just your average shit and piss factory.
You're wrong, though. The whole point of this kind of filter is that it develops its rules based on the information that you give it, not what somebody else thinks. If you tell it that mails from your legitimate business partners aren't spam, it learns to tell them apart. I use a Bayesian filter on my mail, and it has no trouble telling my legitimate business mail, like messages from Amazon about books I've been waiting for, from illegitimate ones. Some of that is that the legitimate mail is written with a very different style from the illegitimate stuff, but I assume that the filter has also learned that mail with amazon.com as the sender is OK. In any case, I find that it just plain works.
There's no point in questioning authority if you aren't going to listen to the answers.
Read the referenced article. The only way to avoid the filter is to make your email sound like a normal message. In essence, the filter recognizes the sales pitch. If you remove the sales pitch to get your spam past the filter, you've removed the whole point of sending the spam.
"The legitimate powers of government extend only to such acts as are injurious to others." Thomas Jefferson.
Just because it's the first one that actually makes the slashdot frontpage it doesn't mean it's the only one.
Do a freshmeat search for bayespam, bogofilter and spamprobe, they're all working and quite mature bayesian filters (or should we say "paulgrahamian" in order to appease the "true bayesian" crowd). Hell, even a search for "bayes" will turn out a few more hits, like ifilter, which aims to automatically classify mail in different folders, but could be easily tuned to filter out spam.
Of these, I think spamprobe is becoming the true "swiss army knife" of "bayesian" filtering; I did find both bogofilter and bayespam spartan, but they work well. spamprobe, on the other hand, is very actively maintained, is under constant improvement by the author, Brian Burton, and has given me excellent results getting rid of over 90% of my spam.
I am just about to put bogofilter in my mail filtering system. I am thinking about combining this baby with spamassassin, as described here:n g-bogof ilter-with-spam-assassin
http://www.randomhacks.net/2002/09/23/#usi
I will use the pass through option and I can use spamassassin to protect against false positives and to adjust the sensitivity.
BTW: Does anyone know if the number of SPAM and nonSPAM have to be about equivalent or is this accounted for? I have 4000 spam mails in a folder, but just about 500 nonspam mails.
Moritz
In my testing (over the last 30 mins) I discovered that filtering is employed when the POP3 "RETR" (retrieve entire message) command is used but no filtering is done when the equally useful "TOP" (show me the headers and X lines of the body) command is issued by a client.
A huge advantage of also doing the filtering for the TOP command would be that mail clients such as The Bat, Pimmy, JBMail and PocoMail will let you preview all headers while leaving mail on the server (or deleting it, whatever) but without actually downloading the full message bodies.
I try the creative step of prepending common Chinese names, e.g. zhao@chinacenter.com, chen@chinacenter.com, lchen@chinacenter.com, chang@chinacenter.com. Along with a nice "Thank you" for the beautiful picture of the Dalai Lama they sent me, and good wishes that the freedom of information contrary to the PRC's politics continues.
CEE5210S The signal SIGHUP was received.
If this is only intended for client side use then it still doesn't address the issue of all the bandwidth that spam wastes. Wouldn't it just be a better project to help all the idiots close the open relays on their servers? Or maybe require authentication on all SMTP servers?
Does this system know what businesses I've given my credit card to?
Do you understand what a bayesian filter does? It tries to figure out what you consider spam. I don't like dentists sending me advertising junk; bogofilter trashes it. Anything about Esperanto or Project Gutenberg or Linux could probably fly on through, as it's got a lot of words that actually appear in my good email in it. At worst, a couple messages from that business get caught, and then it will recognize that the messages are good based on sender and embedded URL's.
In any case, there tends to be a huge difference between the messages I've got from companies I've given my credit card to and the ones that are sending me spam. Usually, one is quietly informing me of new items for sale, and one is screaming about crap. A bayesian filter can often tell the difference.
With some cleverness, you can use any outside filter with the most recent version (i.e. the develpment fork) of Evolution. They've added the ability to pipe incoming messages to an outside program and read back the exit code. So if the program is written using standard Unixisms- i.e. it reads on standard input and returns a different value depending on whether the incoming message is spam or not- it can be used with Evolution. I know that bogofilter can do this because I'm using it with Evolution and it works pretty well.
There's no point in questioning authority if you aren't going to listen to the answers.
Hm... what about an anti-anti spam filter that mangles the message inserting random misspellings into the spam-identifying words? The bayesian filter would perceive this as a message consisting of many 'unclassified' words, just like a message in some unknown language. Sure, the short words probably haven't got many possible misspellings (cock, c0ck, coock, cokc - hm... starts to look undecipherable ), so they would probably get classified after some time. And this would hopefully lower the spam success ratio. But the possibility still remains...
This is what POPFile is for. Its a pop3 proxy server, it sits between your pop3 client and the server and simply adds a classification to the headers (or the subject line for braindead mail clients).
Currently POPFile is a bit rough on computer newbies, it needs a Perl install and such. However, if you read the forums it is intended to end up as an easily installed executable for windows users and to remain a nifty little perl script for the rest of the platforms where it might come in handy. So when those pesky friends and relatives come asking about all the viagra and farmyard spam they get (and you haven't already set them up on your tightly filtered mail server) set up POPFile for them.
Also, its not just for spam filtering. Think of what you could do if you could go beyond simple rules for your inbox. Want email you think is important forwarded to your phone? Create a category for important email and go through your archives and feed POPFile email you would have wanted forwarded instantly. Create a new folder to recieve those mails and watch it for a few days, retraining POPFile until it is getting reasonably good at putting important mail in there. Now set up your mail system to forward those to your phone. Will it work? I don't know, but based on the results I'm getting, it probably would. How about using it to filter help desk emails?
Bleh!
Noone has mentioned it so far, but Yahoo mail has a Bulk Mail folder. SPAM is automatically sent there, and I have yet to see a single false positive (and false negatives are quite rare as well).
:)
The system works surprisingly well. I checked the FAQ and it doesn't go into any detail about how it works, but I wouldn't doubt if something like this is being used.
I've been thinking, and it seems that this could potentially have a lot of use, aside from Spam filtering. Perhaps a mail client could let you categorize email in general (SPAM, Business-related, forwarded stuff from AOL users, etc), and learn how to spot and organize things.
I'm putting this (either the POPfile or bogofilter) into place with a modified SquirrelMail, just to give it a good run; I might try and modify it to also categorize other types of email, just to see if something like that could work.
I could easily see a mail client (web-based or otherwise) that lets you drag mail to specific folders, and eventually learns how to do this for you (and of course you can always correct it by simply dragging to another folder, which also contributes to the learnig process)...
After reading this article my mind is just spinning with ideas... Bayesian search engines... perhaps speech/voice recognition applications... classifying text/html/doc files... organize songs (processing the lyrics)... ugh, I should stop now
NGWave - Fast Sound Editor for Windows
You can separate the newsletters from the businesses you've opted in to from the penile-enlargement spam. Thats one of the beautiful things about POPFile, it isn't just about spam vs useful mail. In fact, it seems to be more accurate and learn faster when you define categories for all the different types of mail you recieve, not just spam vs inbox.
Bleh!
To put this in simpler terms, consider this scenario, 90% of all all X-rays that have a certain feature are from women with breast cancer. That is an easy statistic to compute; you have the x-rays and you follow up with the patients.
The trick is derive a statement like: "If an x-ray has this feature, the patient has NN % chances of having breast cancer. THAT's useful tor screening, but it doesn't follow from the first statment (without some serious statistical calculations).
Bayes theorem has all sorts of applications in prediction. In the case of E-mail, we can greatly oversimply and say "We found that X% of E-mails with this subject line are Spam." "We conclude that an E-mail with this subject line has Y% odds of being spam." Note that these are two very different statements. If we can find Y for the second statement and set a threshold we're comfortable with, say, 95% then we can create a filter with 95% confidence of correctness; it may well be wrong 5% of the time.
Other responses have done a good job with the math so I won't repeat it here.
Well, there are potentially three points. One is that hopefully after a while the filter will work well enough that you can develop some real confidence in it and you won't have to check every time to see that it's working right. I'm pretty close to that point with bogofilter; I so rarely see any false positives that I can almost afford to flush the messages without checking. Actually, I assume that what I'll really do is to change the rules a bit so that alleged spam is sent to a waiting folder and doesn't even show up in my main inbox.
That gets to point two: now I'll be able to check for spam in batch mode. Instead of going through my inbox every time I look for messages, marking some as spam and reading others, I'll be able to read just about everything in my inbox without worrying about spam. Then once a week I can check my spam box and see if there's actually anything legitimate there. This is going to be faster than doing it every time a new message shows up in my inbox.
I'm not a compulsive mail reader, but for some people this would also be really useful because it would protect them from distractions. They are working on something and then their mailbox beeps them to let them know that a message has arrived. Unfortunately, when they check it out it turns out that their train of thought has been needlessly disrupted by another spam. If they can filter out the spam before the notification while still being alerted promptly when a real message shows up, that's a big win.
There's no point in questioning authority if you aren't going to listen to the answers.
Now we can tell spammers: "All your Bayes are belong to us."
The apple mail client, mentioned in the blurb, works very well with IMAP, that's what impressed me enough that I'm actually using it.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-
Friends don't let friends enable ecmascript.
An interesting idea that I haven't seen discussed is using this concept for more general uses. If we can sort spam from non-spam, how about business from personal? Technical from administrative? All you'd need is multiple databases of word probabilities, the ability to assign emails to multiple categories and a hierarchical method of sorting.
"The legitimate powers of government extend only to such acts as are injurious to others." Thomas Jefferson.
These technologies are interesting, but the problem of spam should be solved at the source. Why should we waste our time, money, CPU and drive space trying to outwit spam with clever software? As has been said before, if you filter spam at the inbox, a lot of resources have already been wasted by the time it arrives.
Spam is anti-social behavior - a perversion of technology to make a quick buck. It's a cancer, and we should try to kill it. If you try to fight it any other way, you will constantly be playing catch-up, as the spammers have technology on their side too.
Actually, irony is generally considered to be "use of words to express something different from and often opposite to their literal meaning".
Sarcasm is often defined as a form of irony (but not necessarily), intended to be cutting/offensive etc.
So while his comment may have been sarcasm, it was also irony.
And I'm not pedantic, I'm pernickety. :-)
Tim
This is a problem for *any* email filter. I think they are trying make better solutions for this very problem. Actually solving it is impossible, but this may approximate a solution better than any other filter.
I don't understand why everyone has so much difficulty with spam. Ever since my yahoo mail got deluged, I abandoned it and set up another account. I only gave it out ONLY to my friends/family (about 60 people in my address book right now), and no one else. I keep another mail alias for online purchases and other sites where I MUST give a real mail address. If my alias address starts getting spam, then I will simply redirect it to it's own folder instead of my inbox, then start using a new one. But I'm very selective about whom I purchase from on the net (read: no porn).
I haven't received any spam in over a year.
Ellis
There is a fine line between being a cultivated citizen and being someone else's crop. - A. J. Patrick Liszkie
Welcome to the future: the mail client in Mac OS X 10.2 uses latent semantic analysis. (This isn't just marketingspeak--my mail folder includes "LSMMap"--LS as in "latent semantic".)
I didn't read the POPFile link. Had I read it, I would have known that POPFile is a POP Proxy. Therefore it is a good candidate for conversion to a standalone executable. In other words, given the lack of standard email hooks on the Windows platform, POPFile cleverly avails itself of the one standard to which mail clients are pretty much forced to adhere - POP3.
.exe, integration with the mail client is still desirable if the user is to categorize mail and thus "teach" the system. I guess the alternative, for naive users, is to ship the proxy with a static table of probabilities which can be periodically updated like virus definitions.
However while the proxy itself can live as an
Actually I didn't forget it. Typically in Bayesian expression the denomonator Pr(D) is dropped, meaning there is no more probabilty of any one email then any other.
How long until we can set up Bayesian by-word filtering on Slashdot comments?
-- Ed Avis ed@membled.com
So, the graduate CS course I'm taking this quarter is Evolutionary Computing, which is all about the convoluted nonlinear multidimensional-search-space problems, and guess what our current homework is? That's right, taking statistics on spam data, and using genetic algorithms to evolve a working spam filter.
Due to one typo and two thinkos in my fitness evaluation function, my algorithm evolves -- within only a few dozen generations -- a solution which looks like this:
And it's right.
You cannot apply a technological solution to a sociological problem. (Edwards' Law)
This seems to be about using strange approaches to spam filtering, but really...a bayesian network seems to be a natural step for a system that henceforth was composed of a series of heuristics with no knowledge of which is more important.
(Why hasn't it been done? Bayesian networks are only taught in AI and statistics classes).
What really interests me is that Spamassasin claims to use a genetic algorithm to rate how likely an e-mail is to be spam.
Mod me down and I will become more powerful than you can possibly imagine!
With the filters you can go offline before checking through the list of suspected spams; that way the URLs don't resolve and the spammers don't know you are there; and you get less spam.
-WolfWithoutAClause
"Gravity is only a theory, not a fact!"Don't tell me you're confusing human stupidity with intelligent SPAM filtering?
BD Phone Home!
Shameless plug. Like you weren't expecting it.
Whoa! Don't tell me you assume that GIFs always come with the email? Hey I've got this bridge, wanna buy one? ;-)
-WolfWithoutAClause
"Gravity is only a theory, not a fact!"The tool we really need to combat spam is a personal tracking database for spamvertised URLs. The idea would be to put every URL adversited by spam into the database and then send DAILY complaints to the level 1 ISP for the host until either
1. The URL no longer works.
2. The ISP responds with proof that the URL owner filed criminal complaints against the spammer.
I, for one, am thoroughly fed up with with the amount of time I have to waste dealing with spam. It's time to make it really painful for any ISP that tollerates it.
An engineer who ran for Congress. http://herbrobinson.us
Weren't we talking about people intelligent enough to be proactive about their SPAM prevention measures?
Now then - what URLs are your e-mail client loading for you?
BD Phone Home!
Shameless plug. Like you weren't expecting it.
Heh. People that annoyed Stalin were exiled to Siberia if they were lucky, and were too important to simply kill. :)
"No problem. I have the capacity to do infinite work so long as you don't mind that my quality approaches zero."-Dilbert
1. Yahoo Mail has an interesting way of dealing with spam - you can "report as spam" any message that comes into your inbox. I suspect that they don't have a human reading these, but instead try to match multiple copies of the same e-mail being reported as spam by multiple people. When you have millions of users, if 10,000 report the same e-mail message as spam, it's probably spam. It would be interesting to have an open source program using P2P technology to do the same thing.
2. Like somebody mentioned above, this could be very useful in categorizing helpdesk e-mails, and even providing some canned automatic repsonses for them. E-mails with the words "forgot", "password" and "can't" and "login" would have a very high probability of being about a user can't logging in for some reason, and could be resolved by an automated "HOWTO" and save a company some man hours.
3. I'm going to try to integrate this into our exchange server at work tomorow if the IT guys will let me mess with it, and if not I'll try to integrate it into my (gasp) outlook exchange client.
This whole methodology is already patented by Microsoft. ANY implementation not licensed by Microsoft is going to be a violation... And now that you know, it is treble damages...
patent 6,161,130
BTW, the current unstable version 2.50 of Spamassassin also utilises a Bayesian filter as one of the rulesets. Pretty cool.
I hate to mention this, but I will anyways.
Popfile was announced here in late August, shortly after the Paul Graham article came out. It was originally closed source, which prompted the creation of multiple other projects. Among them is Spambayes and even my own Pasp (both in python, both open source).
As well, Popfile was announced open source at the end of September...on Slashdot. I know this because it was released under such a license as I was finishing up Pasp.
So yeah. As for how well Popfile categorizes mail into multiple categories, I have not run many tests with multiple category bayesian filtering, though the Spambayes group has, and has discovered that filtering mail based on multiple categories is far less accurate (many false categorizations). In the minimal tests I have done, I find this to be the case as well (we are used to less than 2% FP and FN rates, and with >2 bin categorization, error rates spike easily into the 10% range).
So yeah. Popfile has been announced here no less than 3 times now. I've not seen Spambayes announced at all (they deserve it), and Pasp has also not been announced, though I could care less about that.
So it's really only sensitive to phraseology.
-WolfWithoutAClause
"Gravity is only a theory, not a fact!"The patent claims boil down to using a probabilistic classifier to recognize spam. There are many claims, but they're mostly trivial elaborations. Probabilistic classifiers aren't new, and there's no claim they invented them. And it doesn't look like they had to solve any real technical hurdles to apply it. It's one of the most egregiously obvious patents I've seen in a while.
I say there's only one way to test whether an idea is obvious to people skilled in the field, and that's to pose the problem to people skilled in the field and see if they can find the solution. Anything less is a joke.
Not to diss Horvitz and Heckerman -- they're big names in Bayesian inference and Bayes nets. They've been behind a bunch of solid research.
Great, next we'll see slashcode automoderating based on bayesian probability of a troll. Use leetspeak, go to -1, Offtopic.
Please someone tell me I didn't just give them the idea..
"How can you claim that you are anti-crack, while still writing a window manager?" — Metacity README