Abstract
Information retrieval over peer-to-peer networks is an important task. In order to avoid query message flooding and improve information retrieval performance, clustering the nodes sharing the same kind of interests is a feasible approach. An interest crawling agent utilizing an incremental learning algorithm is proposed to calculate a crawled node’s score, which is used for establishing a node cluster. An active time window is employed to accelerate the query. In order to utilize the node cluster efficiently, we present a ε -greedy query routing strategy. Experimental results show our approach performs well.
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Zhang, H., Liu, P. (2006). A Novel P2P Information Clustering and Retrieval Mechanism. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_40
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DOI: https://doi.org/10.1007/11811305_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37025-3
Online ISBN: 978-3-540-37026-0
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