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Tag-Aware Recommender Systems: A State-of-the-Art Survey

  • Zi-Ke ZhangEmail author
  • Tao Zhou
  • Yi-Cheng ZhangEmail author
Article

Abstract

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related studies and future challenges of tag-aware recommendation algorithms.

Keywords

social tagging systems tag-aware recommendation network-based/tensor-based/topic-based methods 

Supplementary material

11390_2011_176_MOESM1_ESM.pdf (75 kb)
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Copyright information

© Springer Science+Business Media, LLC & Science Press, China 2011

Authors and Affiliations

  1. 1.Institute of Information EconomyHangzhou Normal UniversityHangzhouChina
  2. 2.Web Sciences CenterUniversity of Electronic Science and TechnologyChengduChina
  3. 3.Department of PhysicsUniversity of FribourgFribourgSwitzerland

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