• DocumentCode
    23170
  • Title

    Analysis on the content features and their correlation of web pages for spam detection

  • Author

    Ji Hua ; Zhang Huaxiang

  • Author_Institution
    Dept. of Comput. Sci., Shandong Normal Univ., Jinan, China
  • Volume
    12
  • Issue
    3
  • fYear
    2015
  • fDate
    Mar. 2015
  • Firstpage
    84
  • Lastpage
    94
  • Abstract
    In the global information era, people acquire more and more information from the Internet, but the quality of the search results is degraded strongly because of the presence of web spam. Web spam is one of the serious problems for search engines, and many methods have been proposed for spam detection. We exploit the content features of non-spam in contrast to those of spam. The content features for non-spam pages always possess lots of statistical regularities; but those for spam pages possess very few statistical regularities, because spam pages are made randomly in order to increase the page rank. In this paper, we summarize the regularities distributions of content features for non-spam pages, and propose the calculating probability formulae of the entropy and independent n-grams respectively. Furthermore, we put forward the calculation formulae of multi features correlation. Among them, the notable content features may be used as auxiliary information for spam detection.
  • Keywords
    Internet; content management; entropy; probability; search engines; Internet; Web page correlation; Web spam; content feature analysis; entropy; independent n-grams; multifeatures correlation; page rank; probability formulae; regularity distributions; search engines; search result quality; spam detection; statistical regularities; Electronic mail; Entropy; Feature extraction; Gaussian distribution; Probability distribution; Search engines; content features; feature correlation; spam detection; web spam;
  • fLanguage
    English
  • Journal_Title
    Communications, China
  • Publisher
    ieee
  • ISSN
    1673-5447
  • Type

    jour

  • DOI
    10.1109/CC.2015.7084367
  • Filename
    7084367