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Research on social network discovery algorithm in pervasive sensing environment

机译:普适感知环境下的社交网络发现算法研究

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Considering the real social community network partition approach regardless of the directed and weighted characteristic, we propose a novel algorithm in pervasive sensing environment. The proposed SDOR algorithm is based on the definition of nodes optimal route, community likeness index, community discrete degree index and so on parameters to achieve the sensible partition for directed weighted social community network. We conduct some different types of experiments to verify the scalability, accuracy, and validity of the proposed algorithm. The experimental consequences demonstrate that the accuracy of the algorithm is about 90%, higher than existing models about 10%. In addition, the algorithm has good effectiveness and scalability in other different kinds of network. Copyright © 2016 John Wiley & Sons, Ltd.
机译:考虑到真实的社会社区网络划分方法,无论其定向和加权特征如何,我们提出了一种在普适感知环境中的新算法。提出的SDOR算法是基于节点最优路由,社区相似度指数,社区离散度指数等参数的定义,以实现定向加权社会社区网络的合理划分。我们进行了一些不同类型的实验,以验证所提出算法的可扩展性,准确性和有效性。实验结果表明,该算法的准确度约为90%,高于现有模型的约10%。另外,该算法在其他不同类型的网络中具有良好的有效性和可扩展性。版权所有©2016 John Wiley&Sons,Ltd.

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