BTopicMiner: domain-specific topic mining system for Chinese microblog
LI Jin1,2,ZHANG Hua3,WU Hao-xiong3,XIANG Jun3
1. Information Management Department，Central China Normal University, Wuhan Hubei 430074, China 2. School of Information Engineering, Hubei University for Nationalities, Enshi Hubei 445000,China 3. School of Information Engineering, Hubei University for Nationalities, Enshi Hubei 445000, China
Abstract：As microblog application grows rapidly, how to extract users' interested popular topic from massive microblog information automatically becomes a challenging research area. This paper studied and proposed a topic extraction algorithm of Chinese microblog based on extended topic model. In order to deal with data sparse problem of microblog, the content related microblog text would be firstly clustered to generate synthetic document. Based on the assumption that posting relationship among microblogs implied topical correlation, the traditional LDA (Latent Dirichlet Allocation) topic model was extended to model the posting relationship among microblogs. At last, Mutual Information (MI) measurement was utilized to calculate topic vocabulary after extracting topics by proposing extended LDA topic model for topic recommendation. Furthermore, a prototype system for domain-specific topical mining system, named BTopicMiner, was implemented so as to verify the effectiveness of the proposed algorithm. The experimental result shows that the proposed algorithm can extract topics from microblogs more accurately. Meanwhile, the semantic similarity between automatically calculated topic vocabulary and manually selected topic vocabulary exceeds 75% while automatically calculating topic vocabulary based on MI.
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2012, Vol. 32 
