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 Christopher C Yang

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Average citations per article1.00
Citation Count3
Publication count3
Publication years2012-2014
Available for download2
Average downloads per article193.00
Downloads (cumulative)386
Downloads (12 Months)47
Downloads (6 Weeks)4
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1 published by ACM
April 2014 ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue on Linking Social Granularity and Functions: Volume 5 Issue 2, April 2014
Publisher: ACM
Citation Count: 2
Downloads (6 Weeks): 4,   Downloads (12 Months): 39,   Downloads (Overall): 281

Full text available: PDFPDF
Detecting evolving hidden communities within dynamic social networks has attracted significant attention recently due to its broad applications in e-commerce, online social media, security intelligence, public health, and other areas. Many community network detection techniques employ a two-stage approach to identify and detect evolutionary relationships between communities of two adjacent ...
Keywords: Stochastic Blockmodel, Dynamic Community Detection, Temporal Dirichlet Process

May 2013 SOCIETY '13: Proceedings of the 2013 International Conference on Social Intelligence and Technology
Publisher: IEEE Computer Society
Citation Count: 0

Nowadays thread recommendation is considered to be beneficial to improve the end-user stickiness of an online forum. Given the fact of information overload and the diverse interests of forum users, a recommender system in online forum can satisfy not only forum users' information needs by directing them to what they ...
Keywords: graphical model, personalized recommendation, user interest, reranking method

December 2012 WI-IAT '12: Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Publisher: IEEE Computer Society
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 8,   Downloads (Overall): 105

Full text available: PDFPDF
Recommender system provides users with personalized suggestions of product or information. Typically, recommender systems rely on a bipartite graph model to capture user interest. As an extension, some boosted methods analyze content information to further improve the quality of personalized recommendation. However, due to the prevalence of short and sparse ...
Keywords: graphical model, personalized recommendation, user interest, reranking method

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