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Distributed Data Mining in Peer-to-Peer Networks
July/August 2006 (vol. 10 no. 4)
pp. 18-26
Souptik Datta, University of Maryland, Baltimore County
Kanishka Bhaduri, University of Maryland, Baltimore County
Chris Giannella, University of Maryland, Baltimore County
Ran Wolff, Technion - Israel Institute of Technology
Hillol Kargupta, University of Maryland, Baltimore County
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.
Index Terms:
data mining, distributed computing, peer-to-peer systems, P2P, data analysis
Citation:
Souptik Datta, Kanishka Bhaduri, Chris Giannella, Ran Wolff, Hillol Kargupta, "Distributed Data Mining in Peer-to-Peer Networks," IEEE Internet Computing, vol. 10, no. 4, pp. 18-26, July-Aug. 2006, doi:10.1109/MIC.2006.74
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