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New Technology of Library and Information Service  2014, Vol. 30 Issue (9): 51-57    DOI: 10.11925/infotech.1003-3513.2014.09.07
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Research on Topic Related Recommendation Method for Virtual Reader Community
Hong Liang, Ran Congjing
School of Information Management, Wuhan University, Wuhan 430072, China
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[Objective] To help readers select interested communities from massive reader communities. [Methods] This paper proposes virtual reader community recommendation method based on probabilistic topic model, which builds reader-reader and reader-community relations on different topics by finding latent topics of reader communities, and then recommends reader communities by considering topic similarities of both communities and readers. [Results] Experiments on real data prove that the method can effectively find latent topics of reader communities and accurately recommend virtual reader communities compared with existing recommendation methods. [Limitations] Exist cold start problem of recommendation. [Conclusions] This method helps readers accurately and quickly find interested topic-related virtual reader community, promoting the communication of readers and the development of virtual reader communities.

Key wordsReader community      Recommendation      Probabilistic topic model      Collaborative filtering     
Received: 26 May 2014      Published: 20 October 2014
:  G250  

Cite this article:

Hong Liang, Ran Congjing. Research on Topic Related Recommendation Method for Virtual Reader Community. New Technology of Library and Information Service, 2014, 30(9): 51-57.

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