Weighted clustering of attributed multi-graphs

DOI10.1007/s00607-016-0526-5zbMath1380.05095OpenAlexW2557792717MaRDI QIDQ1700861

George Pallis, Marios D. Dikaiakos, Andreas Papadopoulos

Publication date: 22 February 2018

Published in: Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00607-016-0526-5

zbMATH Keywords

clusteringinformation networksattributed multi-graphs

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Clustering in the social and behavioral sciences (91C20) Small world graphs, complex networks (graph-theoretic aspects) (05C82) Parallel algorithms in computer science (68W10) Graph labelling (graceful graphs, bandwidth, etc.) (05C78) Connectivity (05C40) Signed and weighted graphs (05C22) Distributed algorithms (68W15)

Related Items

Cloud data processing using granular based weighted concept lattice and Hamming distance, Community detection in node-attributed social networks: a survey

Uses Software

• Inc-cluster
• SA-cluster
• gSkeletonClu

Cites Work

• Graph clustering
• Modeling by shortest data description
• Efficient and effective community search
• Clustering large attributed information networks: an efficient incremental computing approach
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