Topic detection in online discussion using non-negative matrix factorization

被引：2
|
作者：
Wu, Zhi-Li [1 ]
Li, Chun-Hung [1 ]
机构：
[1] Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
来源：
PROCEEDING OF THE 2007 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY, WORKSHOPS | 2007年
关键词：
D O I：
10.1109/WI-IATW.2007.117
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
While topic detection based on document corpus has gained significant advances in recent years, the analysis of online discussion is often limited by its terseness and conversational style of writing. Using non-negative matrix factorization, user participation models can be developed to help us gain insights on the latent base topics of online discussions. Furthermore, the factorizations allows an automatic discovery of leaders and sub-communities in the online forum. Results on topic detection in online forum as well as the clustering results of several online forums are given.
引用
收藏
页码：272 / 275
页数：4
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