Fuzzy Systems and its Applications

Fuzzy Systems and its Applications

Enhancing Overlapping Community Detection via Centrality-Weighted Possibilistic Fuzzy C-Means (PFCM) Clustering Algorithm

Document Type : Original Article

Authors
Mohammad Mehdi Keikha
Hassan Rezaei
Department of Computer Science, University of Sistan and Baluchestan, Zahedan, Iran
10.22034/jfsa.2026.577307.1302
Abstract
Detecting overlapping communities in complex networks poses significant challenges in the domain of graph data mining, due to the ambiguous nature of community boundaries and the presence of nodes with multiple memberships. Although Fuzzy C-Means (FCM) clustering algorithms provide an effective tool for modeling this uncertainty, their reliance on probabilistic constraints and sensitivity to initial values limit their performance in the presence of structural noise. In this research, to overcome these limitations and simultaneously leverage the network’s topological features and fuzzy logic, we propose the CW-PFCM (Centrality-weighted Possibilistic Fuzzy C-Means) algorithm. In this approach, network centrality measures are used to guide the initialization process and to modulate the membership matrices within the PFCM algorithm. The integration of the possibilistic approach with fuzzy logic allows the model to make a more precise distinction between meaningful overlaps and outlier nodes. Experimental evaluations on several standard datasets and comparisons with state-of-the-art methods show that the proposed method delivers acceptable and competitive performance in terms of validation metrics such as Normalized Mutual Information (NMI) and Modularity, while maintaining robustness against noise. The findings indicate that incorporating the structural importance of nodes into the fuzzy learning process leads to a more accurate identification of real-world communities.
Keywords
Overlapping Community Detection
Possibilistic Fuzzy Clustering
Structural Uncertainty
Centrality Measures
Complex Network Analysis
Subjects

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Fuzzy Systems and its Applications
Volume 9, Issue 1 - Serial Number 18
Open Access Statement
June 2026
Pages 63-91

  • Receive Date 22 February 2026
  • Revise Date 11 May 2026
  • Accept Date 05 June 2026