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Boiling Down Books, Algorithmically
destinyland writes "A year ago, Aaron Stanton harangued Google over his new project, a web site analyzing patterns in books to generate infallible recommendations. In March he finally finished a prototype which he showed to Google, Yahoo, and Amazon, and he's just announced that he's finally received a big contract which 'gives us a great deal of potential data to work with.' The 25-year-old's original prototype examined over 200 books, plotting 729,000 data points across 30,293 scenes — but its universe of analyzed novels is about to become much, much bigger."
It may be that what makes a book great is hard to identify, but what makes a book really bad is much easier to identify. In that case, such an algorithm won't help with recommending high quality works for you to read, but it could be very useful in saving you from wasting your time with obviously bad books (ie it would help with initial triage).
Remember, there are a lot more bad books than good books, so if you had to go through all the books to find the good ones, then you'd spend most of your time just looking a bad books and rejecting them.
There is one persistent son of a bitch on their forum, Joe, who seems to be their nemesis. I wonder what his angle is.
Other than that, I like their approach - involve the community *really* early on.
Apart from Joe.
Open Source Drum Kit, LPLC deve board - mjhdesigns.com
Typically the way we learn and get good at just about everything is that we go a little bit beyond where we're comfortable and we sustain an effort there. After a while our comfort level moves. Just like if I read enough on one subject typically I'll get caught up with a tangent subject and eventually move into that.
Oh honey look... How cute... an angry slashdotter!
the idea of finding books you should read but don't know about seems a problem particularly poorly suited to an automated solution.
Er... -1,Wrong* : You don't seem to be considering the impact of statistical analysis and Very Large Sets of Data (C)(TM). It's becoming increasingly possible not only to know that 125K other people all over the world bought books B, C and D along with book A that you purchased, but now you can also index and analyse their content so it will be even easier to fine tune.
Imagine this: On the first iteration (first purchase) it can only out-of-the-blue recommend to you those books more consistently purchased along with the one you chose. But on subsequent transactions it can remember what you bought and compare the contents of the books. Now if you bought The Silmarillion, Kontakto and The Unfolding of Language over time, it would be possible to suggest that you read Shakespeare's works in their original Klingon once it realizes that you are equally interested in languages as in fictional civilizations.
I agree with you that the day an algorithm can make value judgements on the artistic merits of any work is still far ahead, but there was just recently a story about this FireFox plug in that sumarizes user reviews. Combine the two and...
* Didn't we have this conversation before, or is it just a popular .sig? If there was a "-1,Wrong" moderation, you would be told that the info is wrong but you would lose any insight provided by a direct reply of somebody that bothers to correct you AND post the right facts. With Slashdot being a discussion forum, it's on its best interest to actually promote discussion so you most likely will never see that mod option implemented.
+Raider of the lost BBS