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Resources search has become a hot research issue in peer-to-peer (P2P) systems. In most unstructured P2P systems with flooding mechanism, with exponential growth of the number of messages, serious network congestion and waste of bandwidth result in low efficiency of resources search. In this paper, we propose an unstructured P2P resources search algorithm based on small-world model, in which peers perform k-means clustering on local resources separately, and then build a few similar-links between peers who own similar clusters and some random-links between non-similar peers. Experiment results demonstrate that our algorithm can effectively shorten the average searching length and get high success rate.