Collaborative filtering with diffusion-based similarity on tripartite graphs

Ming-Sheng Shang, Zi-Ke Zhang, Tao Zhou and Yi-Cheng Zhang

Physica A: Statistical Mechanics and its Applications, 2010, vol. 389, issue 6, 1259-1264

Abstract: Collaborative tags are playing a more and more important role for the organization of information systems. In this paper, we study a personalized recommendation model making use of the ternary relations among users, objects and tags. We propose a measure of user similarity based on his preference and tagging information. Two kinds of similarities between users are calculated by using a diffusion-based process, which are then integrated for recommendation. We test the proposed method in a standard collaborative filtering framework with three metrics: ranking score, Recall and Precision, and demonstrate that it performs better than the commonly used cosine similarity.

Keywords: Recommender systems; Collaborative filtering; Diffusion-based similarity; Collaborative tagging systems; Infophysics (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:389:y:2010:i:6:p:1259-1264

DOI: 10.1016/j.physa.2009.11.041

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