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引用次数: 0

摘要

内部的紧密联系和之间的稀疏联系是社区定义的正确假设。由于这一定义,它已成为近年来大多数研究人员在检测社区中存在的研究目标。本文提出了一种新的社区分组方式,即优先考虑其社区的网络结构,而不是任意增加成员,其唯一的指标是基于模块化的价值。对所建小区的最终结果进行了实验和比较,取得了良好的效果。因此,新算法MuLAN具有更强的鲁棒性,它提供了组成基本成员组的检测作为其第一级社区,并检查其余成员是否也相互连接,从而形成一个强大的社区结构。
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Dynamic Multi Level Approach for Community Detection
A dense connection within and a sparse connection between is what is assume right for a definition of community. It has been an existing research aim for most researcher recently in detecting community due to this definition. This paper proposes a new way of group the community is to give priority on the structure of the network for its community, rather than arbitrary addition of members with its only indicator is based on the value of modularity. Experiment and comparison of end result of found community shown a promising outcome. Hence, the new algorithm, MuLAN, is more robust in providing the detection where it forms the basic group of members as its first level of community and the it will check whether the remaining members are also connected with each other which form a strong structure for the community.
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