Recently among various searching techniques, semantic-based searching has drawn significant attention. In this paper, we propose a novel and efficient search mechanism BF-SKIP (Biased walk, Flooding and Search with K-Iteration Preference). We use Vector Space Model (VSM) and relevance ranking algorithms to construct the overlay network. In BF-SKIP system, the search mechanism is divided into three stages (A, B and C). It significantly reduces the number of redundant messages and the number of visited nodes. Our analysis and simulation results show that the BF-SKIP scheme can outperform GES in terms of higher precision and lower search cost.
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