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Computing
Erschienen in: Computing 10/2020

07.08.2020 | Regular Paper

Improved label propagation algorithm for overlapping community detection

verfasst von: Shi Dong

Erschienen in: Computing | Ausgabe 10/2020

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Abstract

Community detection plays an important role in the analysis of complex networks. However, overlapping community detection in real networks is still a challenge. To address the problems of pre-input parameters and label redundancy, an improved label propagation algorithm (ILPA) that adopts a method based on the influence factor is proposed in this paper. Theoretical analysis and experimental results on both synthetic and real datasets show that the ILPA detects that the overlapping community has higher accuracy compared to other existing methods.
Vorheriger Artikel POF-SVLM: pareto optimized framework for seamless VM live migration
Nächster Artikel Performance analysis of the ubiquitous and emergent properties of an autonomic reflective middleware for smart cities

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Metadaten
Titel
Improved label propagation algorithm for overlapping community detection
verfasst von
Shi Dong
Publikationsdatum
07.08.2020
Verlag
Springer Vienna
Erschienen in
Computing / Ausgabe 10/2020
Print ISSN: 0010-485X
Elektronische ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-020-00836-3

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