Dominance-based rough set approach as a paradigm of knowledge discovery and granular computing

Dominance-based rough set approach (DRSA) permits representation and analysis of all phenomena involving monotonicity relationship between some measures or perceptions. DRSA has also some merits within granular computing, as it extends the paradigm of granular computing to ordered data, specifies a syntax and modality of information granules which are appropriate for dealing with ordered data, and enables computing with words and reasoning about ordered data. Granular computing with ordered data is a very general paradigm, because other modalities of information constraints, such as veristic, possibilistic and probabilistic modalities, have also to deal with ordered value sets (with qualifiers relative to grades of truth, possibility and probability), which gives DRSA a large area of applications.