IWWS: a reliability-based WWW collaborative recommender system

Authors:
Haoyang Che;Jiacai Zhang;Shengquan Yu;Jun Gu
Affiliations:
Institute of Software, The Chinese Academy of Sciences, Beijing, China;College of Information Science, Beijing Normal University, Beijing, China;College of Information Science, Beijing Normal University, Beijing, China;Department of Computer Science, Science & Technology University of Hong Kong
Venue:
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
Year:
2005

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Abstract

Recommender systems using collaborative filtering are a popular technique for reducing information overload and finding products. In this paper, we present a reliability-based WWW collaborative recommender system IWWS (Intelligent Web Wizard System), mainly aiming to attack so-called “Matchmaker” problem in collaborative filtering. The “Matchmaker” problem stems from false assumptions that users are counted only by their similarity and high similarity means good advisers. In order to find good advisers for every user, we construct a matchmaker's reliability mode based on the algorithm deriving from Hits, and apply it in IWWS. Comparative experimental results also show that IWWS contrastively improves performance.