
Collaborative filtering resources - sharpshoot
http://www.paulperry.net/notes/cf.asp
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python_kiss
Great link! Google has some great research publications as well that I
recommened everyone checkout: http://labs.google.com/papers.html

They have an amazing collection of research papers based on their products.
Personally, I recommend "Evaluating similarity measures: a large-scale study
in the Orkut social network" as a preliminary mathematical introduction to
user interfaces.

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amichail
The problem with collaborative filtering is that there's a lot of magic going
on that the user does not understand. Some users like to have more control
over personalized recommendations and social networks can give them that
control.

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python_kiss
That website has some great case studies available on recommender systems
available for finding "music", "content", etc. I would much rather prefer that
a computer do my work than myself. Web users have a terrible attention span so
such a system would work to their benefit by eliminating the need to click-
and-find content. For anyone interested, I expressed my ideas on collaborative
filtering here: http://www.socialdegree.com/2007/01/15/interview-w-shuzakcom-
founder-jawad-shuaib/

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jwp
From what I can tell a lot of this CF stuff starts with a machine learning
algorithm and data about likes/dislikes, making filtering a classification or
search task. Is there something that differentiates it from the usual machine
learning challenges? Like dealing with users interactively, perhaps?

