Research on content-based text retrieval and collaborative filtering in hybrid peer-to-peer networks

Authors:
Shaozi Li;Changle Zhou;Huowang Chen
Affiliations:
School of Computer Science, National University of Defense Technology, Changsha, P.R. China;Department of Computer Science, Xiamen University, Xiamen, P.R. China;School of Computer Science, National University of Defense Technology, Changsha, P.R. China
Venue:
CSCWD'04 Proceedings of the 8th international conference on Computer Supported Cooperative Work in Design I
Year:
2004

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Abstract

Hybrid peer-to-peer architectures use special nodes to provide directory services for regions of the network (“regional directory services”). They are a potentially powerful model for developing large-scale networks of complex digital libraries. This paper presents our recent research work on the new content-based text filtering and collaborative filtering based on hybrid P2P (Peer-to-Peer) networks. From various perspectives, our work focuses on how to share the text content and recommend information based on hybrid P2P networks. Several models are proposed toimplementthe content-based text retrieval and collaborative filtering effectively. These models are then evaluated and validated through implementations and analyses. The results show some advantages of the proposed approach for the content-based filtering algorithm based on lexical chain and collaborative filtering algorithm in hybrid P2P network and potential applications in complex digital libraries and distributed information sharing.