A novel p2p information clustering and retrieval mechanism

Authors:
Huaxiang Zhang;Peide Liu
Affiliations:
Dept. of Computer Science, Shandong Normal University, Jinan, China;Dept. of Information Mangement, Shandong Economic University, Jinan, China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

Citing 4
Cited 0

A local search mechanism for peer-to-peer networks

Proceedings of the eleventh international conference on Information and knowledge management
Content-based retrieval in hybrid peer-to-peer networks

CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Topical web crawlers: Evaluating adaptive algorithms

ACM Transactions on Internet Technology (TOIT)
Automatic Information Organization and Retrieval.

Automatic Information Organization and Retrieval.

Quantified Score

Hi-index	0.00

Visualization

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.