Proposal of personal-value-based item modeling and its application to explanation of recommendation

This paper proposes a personal-value based item modeling, which is used for explaining recommendation. In recent years, studies on improvements of user´s satisfactions for recommender systems by showing process of recommendation have been popular in addition to precision of recommendation. The proposed method extracts personal values of reviewers of a movie as the influence of movie´s attribute on its total evaluation. This paper also examines the applicability of the extracted item model to explain recommendation by collaborative filtering.