Novel applications of information retrieval techniques to peer-to-peer file-sharing systems
P2PIR '06 Proceedings of the international workshop on Information retrieval in peer-to-peer networks
Design of a P2P content recommendation system using affinity networks
Computer Communications
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Peer-to-peer file-sharing systems have hundreds of thousands of users sharing petabytes of data, however, their search functionality is limited. In general, query results contain many references to the same data object. These references are grouped, and the size of the group 驴 the number of references it contains 驴 is the typical ranking metric. Although group size is effective in finding popular data, it works poorly for rare, less popular data. Other ranking functions, such as precision and cosine similarity, are more appropriate in this case. We show the significant performance benefitin finding rare data using these ranking functions through extensive simulation.