• DocumentCode
    3228936
  • Title

    Topic Detection and Tracking for News Web Pages

  • Author

    Mori, Masaki ; Miura, Takao ; Shioya, Isamu

  • Author_Institution
    Dept. of Electr. Eng., Hosei Univ., Tokyo
  • fYear
    2006
  • fDate
    18-22 Dec. 2006
  • Firstpage
    338
  • Lastpage
    342
  • Abstract
    This paper proposes a new approach to observe, summarize and track events from a collection of news Web pages. Given a set of temporal Web pages, we obtain valid times-tamp from Web pages and detect events by means of clustering. Then we track events by using KeyGraph based on the clusters and abstract the clusters by using SuffixTree. We examine some experimental results and show the usefulness of our approach
  • Keywords
    Internet; data mining; information retrieval; Web mining; news Web page tracking; topic detection; Engineering management; Event detection; Informatics; Page description languages; Search engines; Uniform resource locators; Web mining; Web pages; TDT; Web Abstraction; Web Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2747-7
  • Type

    conf

  • DOI
    10.1109/WI.2006.171
  • Filename
    4061390
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3228936