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I need to learn about Matrix Factorization for recommender systems, so I downloaded this paper https://datajobs.com/data-science-repo/Recommender-Systems-[Netflix].pdf but I found it too shallow. It didn't explain the concepts in depth for me. So can you please recommend some good papers/resources to learn about the topic?

I need to learn about them so I can implement a matrix factorization model.

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    $\begingroup$ Mining of Massive Datasets by Anand Rajaram available for free ONLINE $\endgroup$ – user49312 Jul 1 '14 at 11:24
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Matrix factorisation is part of Numerical Linear Algebra (NLA). The following are some useful books in NLA and Data Mining / Statistical Learning.

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You can have a look to http://dl.acm.org/citation.cfm?id=2043956. For more details you can look into Recommender system handbook.

I am working on similar problems. For more details or discussion mail me @ pranav.waila[at]gmail[dot]com.

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    $\begingroup$ Welcome to the site. It is generally better to have your information (eg, your email address) on your userpage rather than in an answer. Can you say a little more about the references you link to, what they contain, etc? $\endgroup$ – gung - Reinstate Monica Jun 23 '14 at 17:58

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