Semantics, Knowledge and Grid, International Conference on (2005)
Nov. 27, 2005 to Nov. 29, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SKG.2005.82
Zhichao Li , Tianjin University, Tianjin 300072, China
Pilian He , Tianjin University, Tianjin 300072, China
Feng Li , Baicheng Works University, Baicheng, China
Ming Lei , Tianjin University, Tianjin 300072, China
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 selfclustering. 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.
P. He, F. Li, M. Lei and Z. Li, "Improving Searching Performance Based on Semantic Correlativity in Peer to Peer Network," 2005 First International Conference on Semantics, Knowledge and Grid(SKG), Beijing, 2005, pp. 20.