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Application Research of Data Mining Techniques in P2P Network

机译:数据挖掘技术在P2P网络中的应用研究

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With the increasingly wide application of Peer-to-Peer, a large amount of data have been accumulated in Peer-to-Peer. Nowadays, in improving the search efficiency and system performance, researchers primarily focus on improving the P2P model, these studies have became bottleneckes in some extent. In this paper, data mining technology is applied to P2P network, and some further improvements based on SWLDRM are done, nodes are clustered based on the features of object stored by K-NN algorithm, applicable decentralized clustering algorithm is designed, new K-Chord modle was constructed, simulation experiments between K-Chord and SWLDRM are done and the result shown that K-Chord has lower maintenance cost and higher search efficiency than SWLDRM.
机译:随着对等体越来越广泛的应用,在对等体中累积了大量数据。如今,在提高搜索效率和系统性能方面,研究人员主要专注于改善P2P模型,这些研究在一定程度上成为瓶颈。在本文中,数据挖掘技术应用于P2P网络,并完成了基于SWLDRM的一些进一步的改进,基于K-NN算法存储的对象的特征来聚集节点,设计了分散的聚类算法,设计了新的K-Chord建造了调制器,完成了K-Chord和SWLDRM之间的仿真实验,结果表明K-Chord具有比SWLDRM更低的维护成本和更高的搜索效率。

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