A local fuzzy method based on “p-strong” community for detecting communities in networks

doi:10.1088/1674-1056/25/6/068901

中国物理B ›› 2016, Vol. 25 ›› Issue (6): 68901-068901.doi: 10.1088/1674-1056/25/6/068901

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇

A local fuzzy method based on “p-strong” community for detecting communities in networks

Yi Shen(沈毅), Gang Ren(任刚), Yang Liu(刘洋), Jia-Li Xu(徐家丽)

1 School of Transportation, Southeast University, Nanjing 210096, China;
2 College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China

收稿日期:2015-11-08 修回日期:2016-02-29 出版日期:2016-06-05 发布日期:2016-06-05
通讯作者: Gang Ren E-mail:rengang@seu.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 51278101 and 51578149), the Science and Technology Program of Ministry of Transport of China (Grant No. 2015318J33080), the Jiangsu Provincial Post-doctoral Science Foundation, China (Grant No. 1501046B), and the Fundamental Research Funds for the Central Universities, China (Grant No. Y0201500219).

A local fuzzy method based on “p-strong” community for detecting communities in networks

Yi Shen(沈毅)^1,2, Gang Ren(任刚)¹, Yang Liu(刘洋)², Jia-Li Xu(徐家丽)²

1 School of Transportation, Southeast University, Nanjing 210096, China;
2 College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China

Received:2015-11-08 Revised:2016-02-29 Online:2016-06-05 Published:2016-06-05
Contact: Gang Ren E-mail:rengang@seu.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 51278101 and 51578149), the Science and Technology Program of Ministry of Transport of China (Grant No. 2015318J33080), the Jiangsu Provincial Post-doctoral Science Foundation, China (Grant No. 1501046B), and the Fundamental Research Funds for the Central Universities, China (Grant No. Y0201500219).

摘要/Abstract

摘要：

In this paper, we propose a local fuzzy method based on the idea of “p-strong” community to detect the disjoint and overlapping communities in networks. In the method, a refined agglomeration rule is designed for agglomerating nodes into local communities, and the overlapping nodes are detected based on the idea of making each community strong. We propose a contribution coefficient b_v^c_i to measure the contribution of an overlapping node to each of its belonging communities, and the fuzzy coefficients of the overlapping node can be obtained by normalizing the b_v^c_i to all its belonging communities. The running time of our method is analyzed and varies linearly with network size. We investigate our method on the computer-generated networks and real networks. The testing results indicate that the accuracy of our method in detecting disjoint communities is higher than those of the existing local methods and our method is efficient for detecting the overlapping nodes with fuzzy coefficients. Furthermore, the local optimizing scheme used in our method allows us to partly solve the resolution problem of the global modularity.

关键词: networks, local fuzzy method, overlapping communities, fuzzy coefficients

Abstract:

Key words: networks, local fuzzy method, overlapping communities, fuzzy coefficients

中图分类号: (Networks and genealogical trees)

89.75.Hc

05.45.Xt (Synchronization; coupled oscillators)

沈毅, 任刚, 刘洋, 徐家丽. A local fuzzy method based on “p-strong” community for detecting communities in networks[J]. 中国物理B, 2016, 25(6): 68901-068901.

Yi Shen(沈毅), Gang Ren(任刚), Yang Liu(刘洋), Jia-Li Xu(徐家丽). A local fuzzy method based on “p-strong” community for detecting communities in networks[J]. Chin. Phys. B, 2016, 25(6): 68901-068901.

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A local fuzzy method based on “p-strong” community for detecting communities in networks

A local fuzzy method based on “p-strong” community for detecting communities in networks

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