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Computing Concept Lattices from Very Sparse Large-Scale Formal Contexts

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Graph-Based Representation and Reasoning (ICCS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8577))

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Abstract

This paper introduces a new algorithm for computing concept lattices from very sparse large-scale formal contexts (input data) where the number of attributes per object is small. The algorithm consists of two steps: generate a diagram of a formal context and compute the concept lattice of the formal context using the diagram built in the previous step. The algorithm is experimentally evaluated and compared with algorithms AddExtent and CHARM-L.

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Authors and Affiliations

  1. University of Pavol Jozef Šafárik, Košice, Slovakia

    Lenka Pisková & Tomáš Horváth

Authors
  1. Lenka Pisková
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  2. Tomáš Horváth
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Corresponding author

Correspondence to Lenka Pisková .

Editor information

Editors and Affiliations

  1. Université Toulouse le Mirail, Toulouse, France

    Nathalie Hernandez

  2. L3S Research Center, Hannover, Germany

    Robert Jäschke

  3. LIRMM, Montpellier, France

    Madalina Croitoru

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© 2014 Springer International Publishing Switzerland

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Pisková, L., Horváth, T. (2014). Computing Concept Lattices from Very Sparse Large-Scale Formal Contexts. In: Hernandez, N., Jäschke, R., Croitoru, M. (eds) Graph-Based Representation and Reasoning. ICCS 2014. Lecture Notes in Computer Science(), vol 8577. Springer, Cham. https://doi.org/10.1007/978-3-319-08389-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-08389-6_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08388-9

  • Online ISBN: 978-3-319-08389-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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