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. © 2014 Springer International Publishing.
Cite
CITATION STYLE
Pisková, L., & Horváth, T. (2014). Computing concept lattices from very sparse large-scale formal contexts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8577 LNAI, pp. 245–259). Springer Verlag. https://doi.org/10.1007/978-3-319-08389-6_20
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
