

From Hackathon to production: building a large scale recommendation engine - derwiki
http://exchange.causes.com/2011/07/causes-tech-a-recommendation-engine-that-could/

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dekayed
Could you recommend some good resources for learning more about collaborative
filtering? I'd love to help hack, but feel like I should learn more first.

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derwiki
Most of what I learned was from Programming Collective Intelligence
(<http://amzn.com/0596529325>). If you're in the Bay Area, Noisebridge has a
self-taught machine learning class that I went to for a while (great group, I
just couldn't make the time commitment).

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seymourz
for most of the fundamentals on Collaborative Filtering, You may check
Chapters 8 and 9 from the following online book.

[https://docs.google.com/viewer?url=http%3A%2F%2Finfolab.stan...](https://docs.google.com/viewer?url=http%3A%2F%2Finfolab.stanford.edu%2F~ullman%2Fmmds%2Fbook.pdf)

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tl10
have you looked at Mahout?
[https://cwiki.apache.org/confluence/display/MAHOUT/Itembased...](https://cwiki.apache.org/confluence/display/MAHOUT/Itembased+Collaborative+Filtering)

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derwiki
Hm, I haven't. This suggests that Mahout might not work well for datasets on
the scale we're dealing with (working toward 1 billion membership rows):

[http://lucene.472066.n3.nabble.com/Mahout-not-giving-
recomme...](http://lucene.472066.n3.nabble.com/Mahout-not-giving-
recommendations-with-large-data-sets-td641249.html)

But that's also an older article, and things might be better. Mahout might be
worth checking out.

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epylinkn
excited!

