Biclustering meets triadic concept analysis

DOI10.1007/s10472-013-9379-1zbMath1302.68253OpenAlexW2088347683MaRDI QIDQ2248533

Mehdi Kaytoue, Sergei O. Kuznetsov, Juraj Macko, Amedeo Napoli

Publication date: 26 June 2014

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

Full work available at URL: https://hal.inria.fr/hal-01101143/file/mk-etal-amai70-2014.pdf

zbMATH Keywords

formal concept analysissimilarity relationtriadic concept analysisN-ary relationsnumerical biclustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Knowledge representation (68T30)

Related Items (5)

Triclusters of close values for the analysis of 3D data ⋮ A knowledge reduction approach for linguistic concept formal context ⋮ Triadic formal concept analysis and triclustering: searching for optimal patterns ⋮ Bireducts with tolerance relations ⋮ Computing triadic generators and association rules from triadic contexts

Uses Software

• ParTriCluster

Cites Work

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• Similarity measures in formal concept analysis
• The ParTriCluster algorithm for gene expression analysis
• Polyadic concept analysis
• Mathematical classification and clustering
• Biclustering Numerical Data in Formal Concept Analysis
• Two FCA-Based Methods for Mining Gene Expression Data
• Comparison of Data Structures for Computing Formal Concepts
• Why can concept lattices support knowledge discovery in databases?
• Comparing performance of algorithms for generating concept lattices
• Formal Concept Analysis for the Identification of Combinatorial Biomarkers in Breast Cancer
• Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery
• Concept Lattices

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