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Improving Louvain Algorithm for Community Detection

机译:改善卢瓦特遗产算法进行社区检测

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摘要

Community is one of the important characteristics of reality network, which can effectively reflect the inner information of network and the relation among nodes. For the division of the community there already had many effective algorithms, the Louvain algorithm based modularity is a more popular community discovery algorithm because it can divide network into different hierarchical community structure quickly and efficiently. But, with the increasing size of network, the Louvain algorithm still has a serious problem that has relatively high time complexity in handling massive data. Faced with this situation, in this paper we ensure the merit of the Louvain algorithm and combine with the LPA algorithm which has advantage of effectiveness, proposing an improved algorithm integrating the Louvain algorithm with the LPA algorithm. Through later experiments, the improved algorithm can obviously decrease time complexity, reduce execution time, and ensure the result accuracy compared to original Louvain algorithm.
机译:社区是现实网络的重要特征之一,可以有效地反映网络的内部信息和节点之间的关系。对于社区的划分已经有许多有效的算法,基于Louvain算法的模块化是一种更受欢迎的社区发现算法,因为它可以快速有效地将网络分成不同的分层社区结构。但是,随着网络幅度越来越大,Louvain算法仍然存在严重的问题,在处理大规模数据方面具有相对较高的时间复杂性。面对这种情况,在本文中,我们确保了Louvain算法的优点,并与具有有效性的LPA算法的LPA算法组合,提出了一种利用LPA算法集成了LOUVAIN算法的改进算法。通过后来的实验,改进的算法可以明显降低时间复杂度,减少执行时间,并确保与原始Louvain算法相比的结果准确性。

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