A Study on Additional Information Utilization in Collaborative Filtering by Three-mode Co-clustering

Abstract

The performance of collaborative filtering (CF) can be improved by utilizing not only user-item cooccurrence information but also additional information. This paper improves co-clustering-based CF by introducing three-mode fuzzy co-clustering, which utilizes the conventional user-item cooccurrence information in conjunction with additional genre information on each item. User-item co-clusters are extracted so that preference tendencies of users on items are considered with their intrinsic preferences on genre categories. Then, the recommendation capability of co-clustering-based CF is expected to be improved even when cooccurrence information is quite sparse. In numerical experiments with MovieLens benchmark data, recommendation performance is demonstrated to be improved by properly increasing the responsibility degree of genre information.