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Concept Lattice Reduction by Singular Value Decomposition

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 matrix with fewer dimensions as an input for some known algorithms for lattice construction. Results are presented by visualising neural network. Neural network is responsive for reducing result dimension to two dimensional space and we are able to present result as a picture that we are able to analyse.