Interesting pattern mining in multi-relational data

DOI10.1007/s10618-013-0319-9zbMath1294.68073OpenAlexW1974067702MaRDI QIDQ740605

Eirini Spyropoulou, Tijl De Bie, Mario Boley

Publication date: 3 September 2014

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

Full work available at URL: https://doi.org/10.1007/s10618-013-0319-9

zbMATH Keywords

pattern mininginterestingness measuresK-partite graphsmaximum entropy modellingmulti-relational data mining

Mathematics Subject Classification ID

Database theory (68P15) Data structures (68P05) Information storage and retrieval of data (68P20)

Related Items (3)

Subjective interestingness of subgraph patterns ⋮ Triadic formal concept analysis and triclustering: searching for optimal patterns ⋮ On closure operators related to maximal tricliques in tripartite hypergraphs

Uses Software

• gSpan
• Algorithm 457
• CloseGraph
• LCM

Cites Work

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• Krimp: mining itemsets that compress
• Maximum entropy models and subjective interestingness: an application to tiles in binary databases
• Listing closed sets of strongly accessible set systems with applications to data mining
• The maximum clique problem
• Polyadic concept analysis
• Generating All Maximal Independent Sets: NP-Hardness and Polynomial-Time Algorithms
• Computing Supports of Conjunctive Queries on Relational Tables with Functional Dependencies
• Algorithm Theory - SWAT 2004
• Discovery Science
• Discovery Science
• Algorithm 457: finding all cliques of an undirected graph

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