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An Improved Neighbor Selection Algorithm in Collaborative Filtering Taek-Hun KIM Sung-Bong YANG Publication IEICE TRANSACTIONS on Information and Systems Vol.E88-D No.5 pp.1072-1076 Publication Date: 2005/05/01 Online ISSN: DOI: 10.1093/ietisy/e88-d.5.1072 Print ISSN: 0916-8532 Type of Manuscript: LETTER Category: Contents Technology and Web Information Systems Keyword: recommender system, neighbor selection algorithm, collaborative filtering, Full Text: PDF(120.4KB)>>
Summary: Nowadays, customers spend much time and effort in finding the best suitable goods since more and more information is placed on-line. To save their time and effort in searching the goods they want, a customized recommender system is required. In this paper we present an improved neighbor selection algorithm that exploits a graph approach. The graph approach allows us to exploit the transitivity of similarities. The algorithm searches more efficiently for set of influential customers with respect to a given customer. We compare the proposed recommendation algorithm with other neighbor selection methods. The experimental results show that the proposed algorithm outperforms other methods. | ||||||||||
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