Leveraging the state-of-the-art information retrieval (IR) algorithms and relevance ranking algorithm, we propose an architecture for efficient search in peer-to-peer networks. The key idea is to employ a distributed, content-based algorithm to arrange the participating nodes into semantic clusters, in which most connections are short-distance, connecting pairs of nodes with similar contents. Nodes in different clusters are connected through long-distance links. Queries are routed to the cluster which has the most relevance contents and flooded to the nodes in the corresponding clusters. The experiment results show that the proposed architecture can achieve high recall rate with small cost of network traffic and query processing load.
['Xiaoyu Yang', 'Yiming Hu']
Search Enhanced by Distributed Semantic Clustering in Gnutella-like P2P Systems