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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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
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