Method of Neighborhood Formation in Collaborative Filtering
LENG Ya-Jun1,2, LIANG Chang-Yong1,2, DING Yong1, LU Qing3
1.School of Management, Hefei University of Technology, Hefei 230009
2.Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009
3.College of Economics and Management, Shanghai University of Electric Power, Shanghai 201300
In collaborative filtering, sparsity in ratings makes inaccurate neighborhood formation, thereby resulting in poor recommendations. To address this issue, a method of neighborhood formation, two-phase neighbor selection method (TPNS), is proposed. The definition of neighbor tendency is given. Based on the neighbor tendency, the preliminary neighborhood is formed. Then, the equivalence relation similarity is applied to modify the preliminary neighborhood, which makes the neighborhood formation more accurate. Experimental results on MovieLens dataset show that compared with the existingalgorithms, TPNS performs better in the application of personalized recommendation.
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2013, Vol. 26 
