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引用次数: 4

摘要

社区查找算法努力寻找社区内部比社区之间具有更高连通性的社区。最近引入了一种称为社区集空间的框架,它提供了一种衡量社区集质量的方法。我们提出了一种新的社区查找算法CHI,旨在最大限度地减少该框架定义的违规行为。本文将证明CHI算法与kmeans算法有相似之处。它是灵活和快速的,也可以调整,以找到某些类型的社区。它针对社区集框架和结果进行了优化,因此它比该框架中的其他算法执行得更好。
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Community finding within the community set space
Community finding algorithms strive to find communities that have a higher connectivity within the communities than between them. Recently a framework called the community set space was introduced which provided a way to measure the quality of community sets. We present a new community finding algorithm, CHI, designed to minimize the violations defined by this framework. It will be shown that the CHI algorithm has similarities to kmeans. It is flexible and fast and can also be tuned to find certain types of communities. It is optimized for the community set framework and results so that it performs better than other algorithms within that framework.
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