Résumé
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.