[NRG] Notification: Explanation Strategies for Matrix Factorization Recommend... @ Mon Dec 11, 2017 11am - 12pm (NRG at BU)

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Title: Explanation Strategies for Matrix Factorization Recommender Systems  
(Bashir Rastegarpanah)
Recommender systems are taking on an increasing role in shaping the impact  
of computing on society, and it is consequently important
to develop methods for explaining the recommendations made by such systems.  
In this talk, I will introduce some explanation strategies
for collaborative filtering algorithms that use matrix factorization  
We look for explanations that increase the transparency of the system. To  
do so, we propose two measures. First, we show a model that
describes the contribution of each previous rating given by a user to the  
generated recommendation. Second, we measure the influence of
changing each previous rating of a user on the outcome of the recommender  
system. We show that under the assumption that there are
many more users in the system than there are items, we can efficiently  
generate each type of explanation by using linear approximations
of the recommender system’s behavior for each user, and computing partial  
derivatives of predicted ratings with respect to each user’s known
ratings. At the end, I will demonstrate some examples of generated  
explanations for recommended movies using MovieLens dataset.
When: Mon Dec 11, 2017 11am – 12pm Eastern Time
Where: MCS148
Calendar: NRG at BU
     * Nabeel Akhtar - creator

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