Effectively Detecting Communities by Adjusting Initial Structure via Cores

Joint Authors

Leng, Mingwei
Chen, Mei
Yang, Zhichong
Wen, Xiaofang
Zhang, Mei
Li, Ming

Source

Complexity

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-20, 20 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-11-03

Country of Publication

Egypt

No. of Pages

20

Main Subjects

Philosophy

Abstract EN

Community detection is helpful to understand useful information in real-world networks by uncovering their natural structures.

In this paper, we propose a simple but effective community detection algorithm, called ACC, which needs no heuristic search but has near-linear time complexity.

ACC defines a novel similarity which is different from most common similarity definitions by considering not only common neighbors of two adjacent nodes but also their mutual exclusive degree.

According to this similarity, ACC groups nodes together to obtain the initial community structure in the first step.

In the second step, ACC adjusts the initial community structure according to cores discovered through a new local density which is defined as the influence of a node on its neighbors.

The third step expands communities to yield the final community structure.

To comprehensively demonstrate the performance of ACC, we compare it with seven representative state-of-the-art community detection algorithms, on small size networks with ground-truth community structures and relatively big-size networks without ground-truth community structures.

Experimental results show that ACC outperforms the seven compared algorithms in most cases.

American Psychological Association (APA)

Chen, Mei& Yang, Zhichong& Wen, Xiaofang& Leng, Mingwei& Zhang, Mei& Li, Ming. 2019. Effectively Detecting Communities by Adjusting Initial Structure via Cores. Complexity،Vol. 2019, no. 2019, pp.1-20.
https://search.emarefa.net/detail/BIM-1133353

Modern Language Association (MLA)

Chen, Mei…[et al.]. Effectively Detecting Communities by Adjusting Initial Structure via Cores. Complexity No. 2019 (2019), pp.1-20.
https://search.emarefa.net/detail/BIM-1133353

American Medical Association (AMA)

Chen, Mei& Yang, Zhichong& Wen, Xiaofang& Leng, Mingwei& Zhang, Mei& Li, Ming. Effectively Detecting Communities by Adjusting Initial Structure via Cores. Complexity. 2019. Vol. 2019, no. 2019, pp.1-20.
https://search.emarefa.net/detail/BIM-1133353

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1133353