Peer-to-Peer Usage Analysis: a Distributed Mining Approach

Florent Masseglia 1 Pascal Poncelet 2 Maguelonne Teisseire 2
1 AxIS - Usage-centered design, analysis and improvement of information systems
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Paris-Rocquencourt
2 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : With the huge number of information sources available on the Internet, Peer-to-Peer (P2P) systems offer a novel kind of system architecture providing the large-scale community with applications for file sharing, distributed file systems, distributed computing, messaging and real-time communication. P2P applications also provide a good infrastructure for data and compute intensive operations such as data mining. In this paper we propose a new approach for improving resource searching in a dynamic and distributed database such as an unstructured P2P system. This approach takes advantage of data mining techniques. By using a genetic-inspired algorithm, we propose to extract patterns or relationships occurring in a large number of nodes. Such a knowledge is very useful for proposing the user with often downloaded or requested files according to a majority of behaviors. It may also be useful in order to avoid extra bandwidth consumption.
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https://hal.archives-ouvertes.fr/hal-00106798
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Submitted on : Monday, October 16, 2006 - 2:23:49 PM
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  • HAL Id : hal-00106798, version 1

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Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire. Peer-to-Peer Usage Analysis: a Distributed Mining Approach. AINA: Advanced Information Networking and Applications, 2006, Vienna, Austria. ⟨hal-00106798⟩

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