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Improving Searching Performance Based on Semantic Correlativity in Peer to Peer Network

8 years 8 months ago
Improving Searching Performance Based on Semantic Correlativity in Peer to Peer Network
Most existing Peer-to-peer (P2P) systems support only title-based searches, which can not satisfy the content searches. In this paper, we proposed a semantic correlativity model which can support semantic content-based searches. Firstly, using VSM to represent content and using KNN algorithm to implement self-clustering. Secondly, based on framework, accessing to compute semantic similarity, SCRA policy is proposed to improve routing performance with prefetch technology. By this model, routing overhead can be greatly reduced. At last, preliminary simulation results show that SCRA achieves a great routing performance over the previous algorithms.
Zhichao Li, Pilian He, Feng Li, Ming Lei
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where SKG
Authors Zhichao Li, Pilian He, Feng Li, Ming Lei
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