Microsoft R&D, Israel A Hybrid Explanations Framework for Collaborative Filtering Recommender Systems

Shay Ben-Elazar1,2, Noam Koenigstein1 1. Microsoft R&D, Israel 2. Department of Computer Science, Tel Aviv University, Israel

• Explanations accompanying a recommendation attempt to increase a user’s confidence, help him make good purchase decisions faster, persuade him and attempt to increase the ease of usability or enjoyment in the system1 .

• CF systems tend to draw on item similarity in latent space which has several major drawbacks and tend to be vague or confusing.

• We utilize hand curated meta-data labels and implement a set of algorithms which given a user’s history and recommended item find a satisfying explanation in a “lowest commend denominator” approach.

1) Based on “A Survey of Explanations in Recommender Systems”, Masthoff et.al 2007

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