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Parallel overlapping community discovery based on grey relational analysis

机译:基于灰色关联分析的并行重叠社区发现

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Discovering social communities or social circles from social networks is interesting and important for many applications like business advertisement, social recommendation and collaborative office. In this paper, by integrating grey relational analysis with the label propagation algorithm and the parallel framework, a new parallel algorithm for detecting overlapping communities is proposed. The similarity of the vertices is measured by the grey relational degree and the parallel computation primitives are employed to propagate the labels in parallel. The experiments on both the artificial and realworld networks demonstrate that the new algorithm is effective in detecting overlapping social communities.
机译:从社交网络中发现社交社区或社交圈对于商业广告,社交推荐和协作办公室等许多应用而言非常有趣且重要。本文通过将灰色关联分析与标签传播算法和并行框架相结合,提出了一种新的检测重叠社区的并行算法。顶点的相似性通过灰色关联度来衡量,并采用并行计算基元来并行传播标签。在人工和现实世界网络上的实验表明,该新算法可有效检测重叠的社会社区。

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