• DocumentCode
    768770
  • Title

    Distributed Data Mining in Peer-to-Peer Networks

  • Author

    Datta, Souptik ; Bhaduri, Kanishka ; Giannella, Chris ; Wolff, Ran ; Kargupta, Hillol

  • Author_Institution
    Maryland Univ., Baltimore, MD
  • Volume
    10
  • Issue
    4
  • fYear
    2006
  • Firstpage
    18
  • Lastpage
    26
  • Abstract
    Peer-to-peer (P2P) networks are gaining popularity in many applications such as file sharing, e-commerce, and social networking, many of which deal with rich, distributed data sources that can benefit from data mining. P2P networks are, in fact, well-suited to distributed data mining (DDM), which deals with the problem of data analysis in environments with distributed data, computing nodes, and users. This article offers an overview of DDM applications and algorithms for P2P environments, focusing particularly on local algorithms that perform data analysis by using computing primitives with limited communication overhead. The authors describe both exact and approximate local P2P data mining algorithms that work in a decentralized and communication-efficient manner
  • Keywords
    data analysis; data mining; distributed databases; peer-to-peer computing; P2P networks; data analysis; distributed data mining; e-commerce; file sharing; peer-to-peer networks; social networking; Ad hoc networks; Data analysis; Data mining; Data privacy; Distributed computing; Distributed decision making; Motion pictures; Network servers; Peer to peer computing; Social network services; P2P; data analysis; data mining; distributed computing; peer-to-peer systems;
  • fLanguage
    English
  • Journal_Title
    Internet Computing, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7801
  • Type

    jour

  • DOI
    10.1109/MIC.2006.74
  • Filename
    1704752