A framework for clustering massive graph streams

DOI10.1002/sam.10090OpenAlexW2072099315MaRDI QIDQ4969739

Yuchen Zhao, Philip S. Yu, Charu C. Aggarwal

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.10090

zbMATH Keywords

clusteringgraphsdata mining

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Uses Software

• gSpan
• Xproj
• CloseGraph
• XRules

Cites Work

• Unnamed Item
• Cure: An efficient clustering algorithm for large databases
• Managing and mining graph data
• Random Sampling in Cut, Flow, and Network Design Problems
• Mining Graph Data
• Finding Groups in Data
• An Efficient Heuristic Procedure for Partitioning Graphs
• A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
• Graph Clustering and Minimum Cut Trees
• An improved data stream summary: the count-min sketch and its applications

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