Gal Lavee: "Recommendation Systems"

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Recommendation systems are ubiquitous in our day to day lives. This domain lies at the intersection of academic and industry interests, with examples of fruitful collaborations abounding. In this talk I will motivate the field of automated recommendation systems and give short introduction to common approaches including content-based and Matrix Factorization for collaborative filtering. I will also discuss evaluation methods for recommendation algorithm results.

I will conclude with a description of and results from recent published work on integrating side information, namely user web browsing interaction, to improve Matrix Factorization based recommendation.

Date and Time: 
Thursday, November 24, 2016 - 13:30 to 14:30
Speaker: 
Gal Lavee
Location: 
IDC, C.110
Speaker Bio: 

Gal Lavee, Microsoft.