Knowledge extraction from L-fuzzy contexts associated with criteria evolving over time

Abstract

Information extracted from L-fuzzy contexts is substantially improved by taking into account different points of view, which can roughly be represented by criteria. This work addresses the general study of L-fuzzy contexts were a set of criteria is introduced, analyzing situations in which their evolution over time is known. The relationship among criteria is also an important point in the study. In this sense, the treatment will vary depending on whether they are independent criteria or there exists dependency among them. Of special importance will be those elements that stand out for presenting a positive temporal evolution. Four algorithms are proposed in order to analyze the different situations. Finally, the applicability of the results is shown thought an example where the opinion of the clients of several hotels is analyzed taking into account both the type of traveler considered and the different aspects of the establishments on which a score is given.