A Live-User Study Of Opinionated Explanations For Recommender Systems

This paper describes an approach for generating rich and compelling explanations in recommender systems, based on opinions mined from user-generated reviews. The explanations highlight the features of a recommended item that matter most to the user and also relate them to other recommendation alternatives and the user`s past activities to provide a context.