• DocumentCode
    2539708
  • Title

    Topical Crawler based on multi-level vector space model and optimized hyperlink chosen strategy

  • Author

    Xu, Yang ; Ai-na, Sui ; Zhan-kun, Tang

  • Author_Institution
    Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
  • fYear
    2010
  • fDate
    7-9 July 2010
  • Firstpage
    430
  • Lastpage
    435
  • Abstract
    In this study, through researching and analyzing the technology of Topical Crawler, we improve the critical algorithm, and present the Topic-Relevance judgment algorithm based on Multi-Level Vector Space Model and the Topical Search Strategy based on the content evaluation, which combine with the simple link structure analysis and link tags data analysis. Through the analysis of the experimental data, the algorithm and the strategy proposed in this research have higher accuracy and efficiency, which can improve the performance of the Traditional Topical Crawler greatly.
  • Keywords
    Web services; data analysis; optimisation; query formulation; relevance feedback; data analysis; hyperlink chosen strategy; link tags; multi-level vector space model; optimisation; topic-relevance judgment algorithm; topical crawler; topical search strategy; Algorithm design and analysis; Analytical models; Computational modeling; Crawlers; Queueing analysis; Search engines; Web pages; Multi-Level Vector Space Model; Topic-Relevance; Topical Crawler; Topical Search Strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8041-8
  • Type

    conf

  • DOI
    10.1109/COGINF.2010.5599702
  • Filename
    5599702