I/O efficient structural clustering and maintenance of clusters for large-scale graphs

• Published in: Expert systems with applications Vol. 168; p. 114221
• Main Authors: Seo, Jung Hyuk, Kim, Myoung Ho
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.04.2021; Elsevier BV
• Subjects: Algorithms; Cluster maintenance; Clustering; Dynamic graph; Graph; Graph theory; Graphs; I/O-efficient algorithm; Maintenance costs; Nodes; Structural graph clustering; Cluster maintenance; Structural graph clustering; Graph; Dynamic graph; I/O-efficient algorithm
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2020.114221

In recent years, the size of graph data has increased significantly, but most existing graph clustering algorithms do not consider the case where the size of main memory is not sufficient to handle large amount of graph data. Exploring entire region of graph for clustering causes too many random dis...