Mining closed patterns in relational, graph and network data

DOI10.1007/s10472-012-9324-8zbMath1357.68169OpenAlexW2095398376MaRDI QIDQ2248524

Luc De Raedt, Gemma C. Garriga, Roni Khardon

Publication date: 26 June 2014

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-012-9324-8

zbMATH Keywords

algorithmsnetworksgraphsrelational dataclosed relational patterns

Mathematics Subject Classification ID

Database theory (68P15) Learning and adaptive systems in artificial intelligence (68T05) Logic in artificial intelligence (68T27) Semantics in the theory of computing (68Q55)

Related Items

Mining closed patterns in relational, graph and network data ⋮ Graph-FCA: an extension of formal concept analysis to knowledge graphs

Uses Software

• gSpan
• CLOSET
• CloseGraph

Cites Work

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• Effective feature construction by maximum common subgraph sampling
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• Horn axiomatizations for sequential data
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• On maximal frequent and minimal infrequent sets in binary matrices
• Mining closed patterns in relational, graph and network data
• Logical and Relational Learning
• Inductive Logic Programming: Theory and methods
• Inductive Logic Programming
• Inductive Logic Programming
• Discovery Science
• Inductive Logic Programming
• Concept Lattices
• Learning logic programs with structured background knowledge

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