ABACUS: frequent pattern mining-based community discovery in multidimensional networks

DOI10.1007/s10618-013-0331-0zbMath1281.68173arXiv1303.2025OpenAlexW2963155478WikidataQ56601138 ScholiaQ56601138MaRDI QIDQ2435685

Michele Berlingerio, Francesco Calabrese, Fabio Pinelli

Publication date: 19 February 2014

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1303.2025

zbMATH Keywords

social network analysiscommunity discoverymultidimensional networks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (11)

Comparison of communities detection algorithms for multiplex ⋮ A survey of community detection methods in multilayer networks ⋮ Modularity-based selection of the number of slices in temporal network clustering ⋮ Efficient algorithms to identify periodic patterns in multiple sequences ⋮ Flexible constrained sampling with guarantees for pattern mining ⋮ Local community detection in multilayer networks ⋮ Ensemble-based community detection in multilayer networks ⋮ Failure risk propagation and protection schemes in coupled systems ⋮ Community detection in node-attributed social networks: a survey ⋮ Unnamed Item ⋮ Community detection in multiplex networks: a seed-centric approach

Uses Software

• gSpan
• GenLouvain
• Eclat
• Apriori

Cites Work

• DETECTION OF SOCIAL INTERACTION IN SMART SPACES
• Community Structure in Time-Dependent, Multiscale, and Multiplex Networks
• The Structure and Function of Complex Networks
• Unnamed Item

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