L-Concept lattices with positive and negative attributes: Modeling uncertainty and reduction of size

In our previous works, we introduced an extension of formal fuzzy concept analysis where attributes were considered as a positive and negative information based on user input. In the present paper, we show that the extension is naturally capable to model uncertainty and we describe a general method to increase that uncertainty in a parametric way. Furthermore, we demonstrate that two methods of concept lattice size reduction, which were thoroughly studied in formal fuzzy concept analysis, become instances of the general method when adapted to our extension.