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Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)
Density-Based Clustering for Similarity Search in a P2P Network
Singapore
May 16-May 19
ISBN: 0-7695-2585-7
Mouna Kacimi, University of Bourgogne, France
Kokou Yetongnon, University of Bourgogne, France
P2P systems represent a large portion of the Internet traffic which makes the data discovery of great importance to the user and the broad Internet community. Hence, the power of a P2P system comes from its ability to provide an efficient search service. In this paper we address the problem of similarity search in a Hybrid Overlay P2P Network which organizes data and peers in a high dimensional feature space. Data and peers are described by a set of features and clustered using a density-based algorithm. We experimentally evaluate the effectiveness of the similarity-search using uniform and zipf data distribution.
Citation:
Mouna Kacimi, Kokou Yetongnon, "Density-Based Clustering for Similarity Search in a P2P Network," ccgrid, pp.57-64, Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06), 2006
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