Title :
Improving Searching Performance Based on Semantic Correlativity in Peer to Peer Network
Author :
Li, Zhichao ; He, Pilian ; Li, Feng ; Lei, Ming
Author_Institution :
Sch. of Electron. Inf. Eng., Tianjin Univ., Tianjin
Abstract :
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.
Keywords :
content-based retrieval; pattern clustering; peer-to-peer computing; telecommunication network routing; KNN algorithm; SCRA policy; VSM; content-based retrieval; data structure; semantic content-based search; semantic correlativity routing algorithm; telecommunication network routing; telecommunication traffic; Content management; Electronic mail; Floods; Information retrieval; Knowledge management; Peer to peer computing; Prefetching; Resource management; Routing; Scalability;
Conference_Titel :
Semantics, Knowledge and Grid, 2005. SKG '05. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2534-2
Electronic_ISBN :
0-7695-2534-2
DOI :
10.1109/SKG.2005.82
