Semi-automatic hot event detection

Authors:
Tingting He;Guozhong Qu;Siwei Li;Xinhui Tu;Yong Zhang;Han Ren
Affiliations:
Software College of Tsinghua University, Beijing, China;Department of Computer Science, Huazhong Normal University, Wuhan, China;School of Mathematics and Statistics, Wuhan University, Wuhan, China;Department of Computer Science, Huazhong Normal University, Wuhan, China;Department of Computer Science, Huazhong Normal University, Wuhan, China;Department of Computer Science, Huazhong Normal University, Wuhan, China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

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Abstract

In this paper, we propose a method to detect hot event automatically. We use all the web pages from Jan 1st 2005 to Dec 31st 2005, and detect new events by using incremental TF-IDF model and incremental cluster algorithm. Based on analysis of the attributes of events, we propose a method to measure the activity of events, then filter and sort the event according to the activity of events; finally a hot event list can be derived.