Martin Polovincak

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Our paper introduces well-known methods for compressing formal context and focuses on concept lattices and attribute implication base changes of compressed formal contexts. In this paper Singular Value Decomposition and Non-negative Matrix Factorisation methods for compressing formal context are discussed. Computing concept lattices from reduced formal(More)
One of the main problems connected with the formal concept analysis and lattice construction is the high complexity of algorithms which plays a significant role when computing all concepts from a huge incidence matrix. In some cases, we only need to compute some of them to test for common attributes. In our research we try to modify an incidence matrix(More)
High complexity of lattice construction algorithms and uneasy way of visualising lattices are two important problems connected with the formal concept analysis. Algorithm complexity plays significant role when computing all concepts from a huge incidence matrix. In this paper we try to modify an incidence matrix using matrix decomposition, creating a new(More)
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