Peer Clustering Based on Incremental Learning in P2P Networks
Hua Zhang, Liu Pei, Huang Shang · 2005
This paper discusses the content-based peer clustering in peer-to-peer networks.Information retrieval based on accurate match of keywords in filenames ignores the document semantics and the similarity between documents.If peers are clustered according to the similarity between their released documents of a special interest topic,and the in- formation query is executed among peers of a specific cluster,the efficiency should be improved.We propose an incre- mental learning approach to peer clustering,and employ an interest crawler agent to calculate a peer's score.Whether a peer joins in a cluster or not is determined by its score.Experimental results demonstrate that clustering of peers in hybrid p2p networks is both accurate and more efficient for irformation retrieval.