Collaborative filtering recommender systems often suffer from the 'Matchmaker' problem, which comes from the false assumption that users are counted only based on their similarity, and high similarity means go...Collaborative filtering recommender systems often suffer from the 'Matchmaker' problem, which comes from the false assumption that users are counted only based on their similarity, and high similarity means good advisers. In order to find good advisers for every user, a matchmaker's reliability mode based on the algorithm deriving from Hits is constructed, and it is applied in the proposed World Wide Web (WWW) collaborative recommendation system. Comparative experimental results also show that our approach obviously improves the substantial performance.展开更多
文摘Collaborative filtering recommender systems often suffer from the 'Matchmaker' problem, which comes from the false assumption that users are counted only based on their similarity, and high similarity means good advisers. In order to find good advisers for every user, a matchmaker's reliability mode based on the algorithm deriving from Hits is constructed, and it is applied in the proposed World Wide Web (WWW) collaborative recommendation system. Comparative experimental results also show that our approach obviously improves the substantial performance.
