User Modeling from Review Browsing History for Personal Values-Based Recommendation
Yasufumi Takama, Suzuto Shimizu · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2020
This paper proposes a personal values-based user modeling method from user’s browsing history of reviews. Personal values-based user modeling and its application to recommender systems have been studied. This approach models users’ personal values as the effect of item’s attributes on their decision making. While existing method obtains a user model from reviews posted by a user, this paper proposes to obtain it from reviews a user consulted for his/her decision making. Methods for determining reviews to present for obtaining user feedback, as well as for selecting items to recommend are proposed, of which effectiveness are shown with user experiments.