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A Self-organized Semantic Clustering Approach for Super-Peer Networks

机译:对等网络的自组织语义聚类方法

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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.
机译:将P2P网络划分为不同的语义簇可以有效地提高搜索效率并增强网络的可伸缩性。本文提出了两种针对分类学层次结构语义空间的基于语义的自组织算法,它们可以根据网络负载动态地将网络划分为不同的语义簇,并具有簇内数据之间的语义关系和簇间的负载平衡。维护良好。实验表明这两种聚类算法具有良好的性能和可伸缩性。

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