Comparing two approaches to creating fuzzy concept lattices

Concept lattices are being used in the area of knowledge discovery and data mining. Since the information used to create a formal context may have some uncertainty associated with it, a variety of methods have been proposed to create fuzzy formal contexts and to transform these into fuzzy concept lattices. This paper reviews two of these methods to creating fuzzy concept lattices: the one-sided thresholding approach and the fuzzy closure operator approach. A simple example is presented to illustrate the differences between the two and then bioinformatics data, specifically using a gene annotation data file, is used to further compare the results from the two approaches.