• DocumentCode
    2183090
  • Title

    Detecting sequences and cycles of Web pages

  • Author

    Narayan, B.L. ; Pal, Sankar K.

  • Author_Institution
    Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India
  • fYear
    2005
  • fDate
    19-22 Sept. 2005
  • Firstpage
    80
  • Lastpage
    86
  • Abstract
    Cycle detection in graphs and digraphs has received wide attention and several algorithms are available for this purpose. While the Web may be modeled as a digraph, such algorithms would not be of much use due to both the scale of the Web and the number of uninteresting cycles and sequences in it. We propose a novel sequence detection algorithm for Web pages, and highlight its importance for search related systems. Here, the sequence found is such that its consecutive elements have the same relation among them. This relation is measured in terms of the positional properties of navigational links, for which we provide a method for identifying navigational links. The proposed methodology does not detect all possible sequences and cycles in the Web graph, but just those that were intended by the creators of those Web pages. Experimental results confirm the accuracy of the proposed algorithm.
  • Keywords
    Web sites; graph theory; sequences; Web graph; Web pages; World Wide Web; cycle detection; digraphs; navigational links; sequence detection algorithm; Algorithm design and analysis; Detection algorithms; Machine intelligence; Navigation; Position measurement; Search engines; Terminology; Web pages; World Wide Web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
  • Print_ISBN
    0-7695-2415-X
  • Type

    conf

  • DOI
    10.1109/WI.2005.53
  • Filename
    1517822