research-article

Overlapping community detection with adaptive density peaks clustering and iterative partition strategy

Authors:

Jianhua XiaoAuthors Info & Claims

Volume 213, Issue PC

https://doi.org/10.1016/j.eswa.2022.119213

Published: 01 March 2023 Publication History

Abstract

The community structure is a collection of individuals with common characteristics that commonly exists in complex networks. The detection of community structures aids in mining information in the network and exploring the evolution mechanism of complex network systems. Compared with other traditional community-detection algorithms, the density peak clustering (DPC) algorithm, which has attracted extensive attention, can detect communities with arbitrary shapes through more efficient and accurate clustering. Although many scholars have proposed improvements to DPC, the proper determination of the cut-off distance d c, which is essential for selecting cluster centers, has generally been ignored. Therefore, in this study, we propose an overlapping community-detection algorithm based on adaptive DPC with an iterative partition strategy known as ODPI, which adaptively selects d c based on different network scales and features. Unlike the DPC algorithm, which manually selects cluster centers, the ODPI algorithm uses an iterative k-means clustering method to select community centers. Extensive experiments have been conducted on both real social networks and synthetic networks to demonstrate that ODPI has satisfactory performance on networks with both a complex structure distribution and complex weight distribution.

Highlights

•

An overlapping community detection algorithm based on adaptive DPC is proposed.

•

The cut-off distance d c is chosen based on different scales and features of networks.

•

A new iterative partition strategy is adopted to help select cluster centers adaptively.

•

The proposed algorithm outperforms the state-of-the-arts on different complex network.

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Cited By

Rashid YBhat J(2024) OlapGNKnowledge-Based Systems10.1016/j.knosys.2023.111163283:COnline publication date: 11-Jan-2024
https://dl.acm.org/doi/10.1016/j.knosys.2023.111163
Hamed Kuwil FAtila Ü(2024)A novel hybridization approach to improve the critical distance clustering algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123298247:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123298
Li FYue QLiu YOuyang HGu F(2024)A fast density peak clustering based particle swarm optimizer for dynamic optimizationExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121254236:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121254
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Index Terms

Overlapping community detection with adaptive density peaks clustering and iterative partition strategy
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Clustering and classification
  2. Information systems applications
    1. Data mining
      1. Clustering

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 213, Issue PC

Mar 2023

1402 pages

ISSN:0957-4174

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Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 March 2023

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Cited By

Rashid YBhat J(2024) OlapGNKnowledge-Based Systems10.1016/j.knosys.2023.111163283:COnline publication date: 11-Jan-2024
https://dl.acm.org/doi/10.1016/j.knosys.2023.111163
Hamed Kuwil FAtila Ü(2024)A novel hybridization approach to improve the critical distance clustering algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123298247:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123298
Li FYue QLiu YOuyang HGu F(2024)A fast density peak clustering based particle swarm optimizer for dynamic optimizationExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121254236:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121254
Wan JZhang KRan WMiao D(2024)A feasible solution model for manifold clusteringEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108635134:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108635
Liu SZhang XMa Y(2024)A hybrid information-based two-phase expansion algorithm for community detection with imbalanced scalesApplied Intelligence10.1007/s10489-024-05424-y54:6(4814-4833)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s10489-024-05424-y

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