A self-organized semantic clustering approach for super-peer networks

被引：0

作者：

Qiao, Baiyou ^{[1
]}

Wang, Guoren ^{[1
]}

Xie, Kexie ^{[1
]}

机构：

[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China

来源：

WEB INFORMATION SYSTEMS - WISE 2006, PROCEEDINGS | 2006年 / 4255卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Partitioning a P2P network into distinct semantic clusters can efficiently increase the efficiency of searching and enhance scalability of the network. In this paper, two semantic-based self-organized algorithms aimed at taxonomy hierarchy semantic space are proposed, which can dynamically partition the network into distinct semantic clusters according to network load, with semantic relationship among data within a cluster and load balance among clusters all well maintained. The experiment indicates good performance and scalability of these two clustering algorithms.

引用

页码：448 / 453

页数：6