• DocumentCode
    2918565
  • Title

    Subtopic Based Topic Evolution Analysis

  • Author

    Liu, Yan ; Lv, Nan ; Luo, Junyong ; Yang, Huijie

  • Author_Institution
    Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou, China
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    168
  • Lastpage
    172
  • Abstract
    Traditional topic tracking approaches can obtain the relevant stories. However, the relationship between stories occurred during the topic developing process can not be exhibited clearly. By analyzing the evolution of the topic, the concept subtopic is put forward and the focus of topic evolution analysis is subtopic instead. Four levels topic model is constructed. The subtopic detection algorithm, time slices partition algorithm and topic evolution analysis algorithm are designed. These algorithms make use of the temporal characteristic of topic, partition the news stories into time slices and compute the similarity of these units. As a result, the relationships between the various subtopics in the process of the topic evolution are achieved. Experiments show our algorithms are effective.
  • Keywords
    text analysis; concept subtopic; subtopic detection algorithm; temporal characteristic; time slices partition algorithm; topic developing process; topic evolution analysis algorithm; topic tracking; Algorithm design and analysis; Clustering algorithms; Data analysis; Data visualization; Detection algorithms; Earthquakes; Information analysis; Information science; Information systems; Partitioning algorithms; subtopic; time slices; topic evolution; topic tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Mining, 2009. WISM 2009. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3817-4
  • Type

    conf

  • DOI
    10.1109/WISM.2009.42
  • Filename
    5369498