A Center-Based Community Detection Method in Weighted Networks

Jie Jin, Lei Pan, Chong-Jun Wang, Junyuan Xie
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引用次数: 10

Abstract

The study of community detection has received more and more attention in recent years, the problem is very difficult and of great importance in many fields such as sociology, biology and computer science. But most of the algorithms proposed so far could not utilize the weight information within weighted networks, and many of them are so time-consuming that they are not fit for the large-scale networks. We propose a new center-based method, which is especially designed for weighted networks. And the method is also suitable for large-scale network because of its low computational complexity. We demonstrate our method on a synthetic network and two real-world networks. The result shows the high efficiency and precision of our method.
加权网络中基于中心的社区检测方法
近年来,社区检测的研究受到越来越多的关注,该问题在社会学、生物学和计算机科学等多个领域都具有重要的意义和难度。但目前提出的大多数算法都不能充分利用加权网络中的权值信息,而且很多算法耗时长,不适合大规模网络。我们提出了一种新的基于中心的方法,该方法是专门为加权网络设计的。该方法计算复杂度低,适用于大规模网络。我们在一个合成网络和两个真实网络上演示了我们的方法。结果表明,该方法具有较高的效率和精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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