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Semi-automatic Hot Event Detection

  • Tingting He
  • Guozhong Qu
  • Siwei Li
  • Xinhui Tu
  • Yong Zhang
  • Han Ren
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)

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.

Keywords

Event Detection News Report Document Frequency Novelty Detection Hellinger Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tingting He
    • 1
    • 2
  • Guozhong Qu
    • 2
  • Siwei Li
    • 3
  • Xinhui Tu
    • 2
  • Yong Zhang
    • 2
  • Han Ren
    • 2
  1. 1.Software College of Tsinghua UniversityBeijingChina
  2. 2.Department of Computer ScienceHuazhong Normal UniversityWuhanChina
  3. 3.School of Mathematics and StatisticsWuhan UniversityWuhanChina

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