• DocumentCode
    2770812
  • Title

    Connecting Sparsely Distributed Similar Bloggers

  • Author

    Agarwal, Nitin ; Liu, Huan ; Subramanya, S. ; Salerno, J.J. ; Yu, Philip S.

  • Author_Institution
    Univ. of Arkansas at Little Rock, Little Rock, AR, USA
  • fYear
    2009
  • fDate
    6-9 Dec. 2009
  • Firstpage
    11
  • Lastpage
    20
  • Abstract
    The nature of the Blogosphere determines that the majority of bloggers are only connected with a small number of fellow bloggers, and similar bloggers can be largely disconnected from each other. Aggregating them allows for cost-effective personalized services, targeted marketing, and exploration of new business opportunities. As most bloggers have only a small number of adjacent bloggers, the problem of aggregating similar bloggers presents challenges that demand novel algorithms of connecting the non-adjacent due to the fragmented distributions of bloggers. In this work, we define the problem, delineate its challenges, and present an approach that uses innovative ways to employ contextual information and collective wisdom to aggregate similar bloggers. A real-world blog directory is used for experiments. We demonstrate the efficacy of our approach, report findings, and discuss related issues and future work.
  • Keywords
    Web sites; Blogosphere; business opportunities exploration; cost-effective personalized services; targeted marketing; Books; Computer science; Conference management; Distributed computing; Engineering management; Joining processes; Meetings; Portals; Publishing; Software engineering; Blogosphere; Long Tail; clustering; collective wisdom; latent semantic analysis; mean average precision (MAP); power law; similar bloggers; sparse distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2009. ICDM '09. Ninth IEEE International Conference on
  • Conference_Location
    Miami, FL
  • ISSN
    1550-4786
  • Print_ISBN
    978-1-4244-5242-2
  • Electronic_ISBN
    1550-4786
  • Type

    conf

  • DOI
    10.1109/ICDM.2009.38
  • Filename
    5360226