Proposal of User Modeling Method Employing Reputation Analysis on User Reviews Based on Personal Values

Abstract

This paper proposes the user modeling method that reflects user's personal values for recommender systems. Existing methods such as collaborative and content-based approach tend to be less-accurate for new users and items owing to the lack of the relation between items and users' preference. Meanwhile, personal values have been taken notice because of its significant relation to potential preferences of users. While existing recommender systems usually employ user preference of items to make recommendations, proposed method focuses on users' personal values, which mean value judgments that show what attributes users put a high priority. By analyzing the relation between ratings for an item and attributes, user's priority on each attribute is extracted as a user model that reflects user's value judgment. The proposed method is applied to customer reviews on Kakaku.com, of which results show that the attributes on which users put high priority can be modeled with less reputation information.