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首页> 外文期刊>International Journal of Modern Physics, B. Condensed Matter Physics, Statistical Physics, Applied Physics >A FAST ESTIMATION ALGORITHM OF COMMUNITY NUMBER IN LARGE SCALE-FREE COMPLEX NETWORKS
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A FAST ESTIMATION ALGORITHM OF COMMUNITY NUMBER IN LARGE SCALE-FREE COMPLEX NETWORKS

机译:大规模免费复杂网络中社区数的快速估计算法

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摘要

In conventional community detecting algorithms, the community number is always a bypass product and cannot be estimated before partitioning. Since partitioning large scale and dynamic complex networks takes exhausting computation, the community number sometimes can be a terminal condition of iterations or a preset optimal parameter for speeding up partitioning algorithms. This paper assumes that communities are organized around the center of core nodes in a scale-free network. A separability function is built to dichotomize nodes into two classes and the class of large degree nodes is selected as the core node candidate set. An improved shortest path seeking algorithm is applied to remove the closest neighbors of a specific core node. The number of remaining core nodes is then the estimated number of communities. Experiments of real world scale-free networks and computer generated networks show that the results are very close to the well-proven results.
机译:在传统的社区检测算法中,社区编号始终是旁路产品,无法在分区之前进行估计。由于对大型动态复杂网络进行划分需要耗费大量计算,因此社区号有时可以是迭代的最终条件,也可以是用于加速划分算法的预设最佳参数。本文假设社区是在无规模网络中围绕核心节点的中心组织的。建立可分离性功能可将节点分为两类,并选择一类高度节点作为核心节点候选集。一种改进的最短路径搜索算法被应用于去除特定核心节点的最近邻居。剩下的核心节点数就是估计的社区数。真实世界的无标度网络和计算机生成的网络的实验表明,该结果非常接近经过充分验证的结果。

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