首页> 外文会议>Dependable, Autonomic and Secure Computing, 2009. DASC '09 >A Hybrid Algorithm for Solving Two-Part Division Problem in Network Community Detection
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A Hybrid Algorithm for Solving Two-Part Division Problem in Network Community Detection

机译:解决网络社区检测中两部分划分问题的混合算法

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Network representation is a convenient and intuitive abstraction for analyzing the massive interacting data. Some topological characteristics of the network have been found in the past decade, and community structure is the typical one of them. Community detection has become a hot topic in complex network analysis. In the paper, a hybrid algorithm is presented for solving such problem. At first, we take the max-degree node as the "core" node. Then, the diffusing operation is per-formed on it to produce two preliminary partitions. Subsequently, an EO-based adjustment step is used for generating the final partitioning with high quality. In addition, four real-world networks are used for validating the efficiency and effectiveness of our hybrid algorithm. The experimental results show that the proposed hybrid algorithm is a promising solution for solving the community detection problem both in precision and efficiency.
机译:网络表示是用于分析大量交互数据的便捷直观的抽象。在过去的十年中,已经发现了该网络的某些拓扑特征,而社区结构就是其中的典型特征之一。社区检测已成为复杂网络分析中的热门话题。本文提出了一种混合算法来解决这一问题。首先,我们将最大度数节点作为“核心”节点。然后,对其执行扩散操作以产生两个初步分区。随后,基于EO的调整步骤用于生成高质量的最终分区。此外,使用四个真实世界的网络来验证我们的混合算法的效率和有效性。实验结果表明,所提混合算法是解决社区检测问题的一种既有精度又有效率的解决方案。

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