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Computing Concept Lattices from Very Sparse Large-Scale Formal Contexts

  • Lenka PiskováEmail author
  • Tomáš Horváth
Conference paper
  • 853 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8577)

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.

Keywords

Frequent Itemsets Concept Lattice Cover Relation Formal Context Formal Concept Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.University of Pavol Jozef ŠafárikKošiceSlovakia

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