Name
Title | ||
|---|---|---|
Improving Searching Performance Based on Semantic Correlativity in Peer to Peer Network |
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. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/SKG.2005.82 | Proceedings - First International Conference on Semantics, Knowledge and Grid, SKG 2005 |
Keywords | Field | DocType |
pattern clustering,semantic correlativity routing algorithm,knn algorithm,great routing performance,data structure,semantic correlativity model,semantic similarity,preliminary simulation result,scra policy,peer network,content search,telecommunication traffic,peer-to-peer computing,telecommunication network routing,prefetch technology,semantic correlativity,semantic content-based search,vsm,content-based retrieval,existing peer-to-peer,computational semantics,satisfiability | k-nearest neighbors algorithm,Semantic similarity,Data mining,Peer-to-peer,Policy-based routing,Computer science,Peer to peer computing,Content based retrieval,Instruction prefetch,Cluster analysis,Distributed computing | Conference |
Volume | Issue | ISSN |
null | null | null |
ISBN | Citations | PageRank |
0-7695-2534-2 | 0 | 0.34 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhichao Li | 1 | 51 | 6.14 |
| Pilian He | 2 | 29 | 7.46 |
| Feng Li | 3 | 0 | 0.34 |
| Ming Lei | 4 | 14 | 4.48 |