An Improved Neighbor Selection Algorithm in Collaborative Filtering

Taek-Hun KIM  Sung-Bong YANG  

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
recommender system,  neighbor selection algorithm,  collaborative filtering,  

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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.