Acta Metallurgica Sinica(English letters) ›› 2013, Vol. 20 ›› Issue (1): 122-128.doi: 10.1016/S1005-8885(13)60018-7

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BPR-UserRec: a personalized user recommendation method in social tagging systems


  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2012-09-18 Revised:2012-12-10 Online:2013-02-28 Published:2013-02-28
  • Supported by:

    This work was supported by the National Basic Research Program of China (2009CB320505), the Hi-Tech Research and Development Program of China (20011AA 01A102), the Nuclear High-Based Project of China (2012ZX01039004-008), the National Nature Science Foundation of China (61002011), and the Electronic Information Industry Development Fund Program ‘The Development and Industrialization of Key Supporting Software in Cloud Computing (Cloud Storage Service)’


Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems (STS) are becoming more and more popular for users to annotate, organize and share items on the Web. Moreover, online social network has been incorporated into social tagging systems. As more and more users tend to interact with real friends on the Web, personalized user recommendation service provided in social tagging systems is very appealing. In this paper, we propose a personalized user recommendation method, and our method handles not only the users’ interest networks, but also the social network information. We empirically show that our method outperforms a state-of-the-art method on real dataset from dataset and Douban.

Key words:

social tagging systems, user recommendation, tensor factorization