A Graph-Based Method for Combining Collaborative and Content-Based Filtering

Authors:
Nguyen Duy Phuong;Le Quang Thang;Tu Minh Phuong
Affiliations:
Faculty of Information Technology, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam;Faculty of Information Technology, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam;Faculty of Information Technology, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
Venue:
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2008

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Abstract

Collaborative filtering and content-based filtering are two main approaches to make recommendations in recommender systems. While each approach has its own strengths and weaknesses, combining the two approaches can improve recommendation accuracy. In this paper, we present a graph-based method that allows combining content information and rating information in a natural way. The proposed method uses user ratings and content descriptions to infer user-content links, and then provides recommendations by exploiting these new links in combination with user-item links. We present experimental results showing that the proposed method performs better than a pure collaborative filtering, a pure content-based filtering, and a hybrid method.