Expertise-based peer selection

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Abstract

Peer-to-Peer systems have proven to be an effective way of sharing data. Finding the data in an efficient and robust manner still is a challenging problem. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic overlay network (SON). Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment we show how expertise based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages.

Original languageEnglish
Title of host publicationSemantic Web and Peer-to-Peer: Decentralized Management and Exchange of Knowledge and Information
PublisherSpringer Berlin / Heidelberg
Pages125-142
Number of pages18
ISBN (Print)3540283463, 9783540283461
DOIs
Publication statusPublished - 2006

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Siebes, R., Haase, P., & Van Harmelen, F. (2006). Expertise-based peer selection. In Semantic Web and Peer-to-Peer: Decentralized Management and Exchange of Knowledge and Information (pp. 125-142). Springer Berlin / Heidelberg. https://doi.org/10.1007/3-540-28347-1_7