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Research on Collaborative Filtering of Heuristic Transitive Similarity Between Items |
Li Linna1, Li Jianchun2, Zhang Zhiping1 |
1. Institute of Scientific&Technical Information of China, Beijing 100038, China; 2. School of Computer & Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450052, China |
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Abstract Aiming at the problem of only finding similar relationship between items rated by common users and enlightened by the transitivity between peoples among social network, this paper figures that the similarity between items also have transitivity. A collaborative filtering algorithm based on heuristic similarity propagation between items is proposed. The experiments indicate that the proposed method can provide better recommendation accuracy by comparing with classic collaborative filtering algorithms.
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Received: 13 November 2012
Published: 29 March 2013
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