Collaborative filtering in social tagging systems based on joint item-tag recommendations

Jing Peng, Daniel Zeng, Huimin Zhao, Fei Yue Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

50 Scopus citations

Abstract

Tapping into the wisdom of the crowd, social tagging can be considered an alternative mechanism - as opposed to Web search - for organizing and discovering information on the Web. Effective tag-based recommendation of information items, such as Web resources, is a critical aspect of this social information discovery mechanism. A precise understanding of the information structure of social tagging systems lies at the core of an effective tag-based recommendation method. While most of the existing research either implicitly or explicitly assumes a simple tripartite graph structure for this purpose, we propose a comprehensive information structure to capture all types of co-occurrence information in the tagging data. Based on the proposed information structure, we further propose a unified user profiling scheme to make full use of all available information. Finally, supported by our proposed user profile, we propose a novel framework for collaborative filtering in social tagging systems. In our proposed framework, we first generate joint item-tag recommendations, with tags indicating topical interests of users in target items. These joint recommendations are then refined by the wisdom from the crowd and projected to the item space for final item recommendations. Evaluation using three real-world datasets shows that our proposed recommendation approach significantly outperformed state-of-the-art approaches.

Original languageEnglish (US)
Title of host publicationCIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages809-818
Number of pages10
DOIs
StatePublished - 2010
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: Oct 26 2010Oct 30 2010

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
CountryCanada
CityToronto, ON
Period10/26/1010/30/10

Keywords

  • Collaborative filtering
  • Explanation
  • Joint recommendation
  • Social tagging
  • Tagging structure

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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    Peng, J., Zeng, D., Zhao, H., & Wang, F. Y. (2010). Collaborative filtering in social tagging systems based on joint item-tag recommendations. In CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops (pp. 809-818). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1871437.1871541