A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Combining semantic and syntactic document classifiers to improve first story detection
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Topic-conditioned novelty detection
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
New event detection based on indexing-tree and named entity
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Topic Detection in Online Discussion Using Non-negative Matrix Factorization
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Topic Detection via Participation Using Markov Logic Network
SITIS '07 Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System
Topic Detection and Tracking for Threaded Discussion Communities
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A model for anticipatory event detection
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
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Many bursty topics which are difficult to summarize and search exist in web forums. Most existing topic detection and tracking (TDT) methods deal with the news stories, but the language used in web forums are much casual, oral and informal compared with news data. In this paper, we present a noise-filtered model to extract bursty topics from web forums using terms and participations of users. Conducting experiments in ShuiMu community we demonstrate the efficiency of our model. Our model not only extracts bursty topics which are better organized for search and visualization, but also discoveries communities corresponding to these topics.