A distributed and incremental algorithm for large-scale graph clustering

Graph clustering is one of the key techniques to understand structures that are presented in networks. In addition to clusters, bridges and outliers detection is also a critical task as it plays an important role in the analysis of networks. Recently, several graph clustering methods are developed a...

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Veröffentlicht in:	Future generation computer systems Jg. 134; S. 334 - 347
Hauptverfasser:	Inoubli, Wissem, Aridhi, Sabeur, Mezni, Haithem, Maddouri, Mondher, Mephu Nguifo, Engelbert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2022 Elsevier
Schlagworte:	Artificial Intelligence Big graph analysis Bioinformatics Community detection Computer Science Distributed, Parallel, and Cluster Computing Graph processing Hubs detection Machine Learning Outliers detection Structural graph clustering Community detection Big graph analysis Structural graph clustering Graph processing Hubs detection Outliers detection
ISSN:	0167-739X, 1872-7115
Online-Zugang:	Volltext
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