• DocumentCode
    1573663
  • Title

    Peer-to-Peer Rating

  • Author

    Bickson, Danny ; Malkhi, Dahlia ; Zhou, Lidong

  • Author_Institution
    Hebrew Univ. of Jerusalem, Jerusalem
  • fYear
    2007
  • Firstpage
    211
  • Lastpage
    218
  • Abstract
    This paper proposes to utilize algorithms from the probabilistic graphical models domain for Peer-to-Peer rating of data items and for computing "social influence" of nodes in a Peer-to-peer social network. We evaluate the practicality of our approach using large- scale simulations over a MSN Live Messenger subgraph consisting of about a million nodes. Our algorithms are general since they can be used for Peer-to-peer monitoring and for the efficient computation of other node ranking methods, such as PageRank and Information Centrality.
  • Keywords
    peer-to-peer computing; social aspects of automation; MSN Live Messenger subgraph; node ranking method; peer-to-peer monitoring; peer-to-peer rating; peer-to-peer social network; probabilistic graphical model domain; social influence computing; Computer networks; Convergence; Cost function; Distributed computing; Graphical models; Iterative algorithms; Motion pictures; Peer to peer computing; Silicon; Social network services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Peer-to-Peer Computing, 2007. P2P 2007. Seventh IEEE International Conference on
  • Conference_Location
    Galway
  • Print_ISBN
    978-0-7695-2986-8
  • Type

    conf

  • DOI
    10.1109/P2P.2007.36
  • Filename
    4343482