Attribute reduction plays an important role in the areas of rough sets and granular
computing. Many kinds of attribute reducts have been defined in previous studies. However …

Rule induction method based on rough set theory (RST) has received much attention
recently since it may generate a minimal set of rules from the decision system for real-life …

This paper uses the Dominance-based Rough Set Approach (DRSA) to formulate airline
service strategies by generating decision rules that model passenger preference for airline …

This study differs from previous ones applying multivariate statistical analysis and multiple
criteria decision-making (MCDM) methods. We use the Variable Consistency Dominance …

Recommender system (RS) can be used to provide personalized recommendations based
on the different tastes of users. Item-based collaborative filtering (IBCF) has been …

Data dependencies in databases and attribute dependencies in decision systems are
important when addressing problems concerning data quality and attribute reduction, in …

Granular computing concerns human thinking and problem solving, as well as their
implications to the design of knowledge intensive systems. It simplifies complex real world …

Rough set approaches to data analysis involve removing redundant attributes, redundant
attribute-value pairs, and redundant rules in order to obtain a minimal set of simple and …

Based on multi-dominance discernibility matrices, a non-incremental algorithm RIDDM and
an incremental algorithm INRIDDM are proposed by means of Dominance-based Rough Set …

Granular computing is an emerging field of study that attempts to formalize and explore
methods and heuristics of human problem solving with multiple levels of granularity and …