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Research Article Open access CC BY 4.0

Similarity-Based Content Retrieval in Self-Organizing Peer-to-Peer Networks

Takuya Yamaguchi, Andrii Zhygmanovskyi, Noriko Matsumoto, Norihiko Yoshida

Journal of Advances in Mathematics and Computer Science · pp. 456–470 · Published 14 Nov 2014

10.9734/BJMCS/2015/14177

Abstract

This paper presents dynamic reorganization of peer-to-peer networks to make query routing and content retrieval efficient. The reorganization is conducted which use content similarity information. Unlike other related studies using semantic proximity, the method proposed in this paper relies on folksonomy, which gained wide use in figuring out content similarity in various social networks. The proposed method is designed primarily for flooding-based unstructured P2P networks, however it also can be applied to structured P2P networks such as Tapestry. Simulation-based experiments confirm the effectiveness of the proposed method.

P2P network reorganization content similarity folksonomy.

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