• DocumentCode
    3637592
  • Title

    Text-Based Web Page Classification with Use of Visual Information

  • Author

    Vladimír Bartík

  • Author_Institution
    Dept. of Inf. Syst., Brno Univ. of Technol., Brno, Czech Republic
  • fYear
    2010
  • Firstpage
    416
  • Lastpage
    420
  • Abstract
    As the number of pages on the web is permanently increasing, there is a need to classify pages into categories to facilitate indexing or searching them. In the method proposed here, we use both textual and visual information to find a suitable representation of web page content. In this paper, several term weights, based on TF or TF-IDF weighting are proposed. Modification is based on visual areas, in which the text appears and their visual properties. Some results of experiments are included in the final part of the paper.
  • Keywords
    "Visualization","Web pages","Classification algorithms","Accuracy","Support vector machine classification","HTML","Equations"
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
  • Print_ISBN
    978-1-4244-7787-6
  • Type

    conf

  • DOI
    10.1109/ASONAM.2010.34
  • Filename
    5563068