Computing Fuzzy Rough Set based Similarities with Fuzzy Inference and Its Application to Sentence Similarity Computations

Since then, it has been of interest both for theoretical researcher and application scientists for applications varying from financial analysis, text summarization, image processing, information retrieval, stock prediction to keyword extraction, feature selection to mention a few. Fuzzy Rough Set (Pawlak, 1982, Jensen and Shen, 2004) was proposed for fuzzification of lower and upper approximation, which in applications to problems is very intuitive and useful, given the fact that each member of the universe bears a membership to the set under consideration. Since, there are two sets in a Rough Set based application namely lower approximation and upper approximation, hence, there are two Fuzzy Sets under study in the domains of Fuzzy Rough Set based analysis. In problems in which two Fuzzy Rough Sets have been computed and compared, how to determine the similarity and other relations between these pairs of Fuzzy Rough Sets? This can be illustrated with the example of application validated in this paper, viz.