Set-valued information systems are generalized models of single-valued information
systems. In this paper, we propose two new relations for set-valued information systems …

A major application of rough set theory is concept analysis for deciding if an object is an
instance of a concept based on its description. Objects with the same description form an …

In rough set theory, a decision class (ie, a subset of objects) is approximated by three pair-
wise disjoint positive, boundary, and negative regions. The concept of three-way decisions …

Reject inference is a credit scoring technique that can resolve sample selection bias, with
several statistical and machine learning methods having been recently employed to infer the …

Abstract Malignant Focal Liver Lesion (FLL) is a main cause of primary liver cancer. In most
existing Computer-Aided Diagnosis (CAD) systems of FLLs, machine learning and data …

Rough set (RS) is a mathematical framework used to deal with incomplete and uncertain
information. It has been widely used in decision analysis, data mining, artificial intelligence …

Numerous linguistically valued facts from the actual world have been modeled using the
fuzzy linguistic approach. Concept lattice theory has the potential to be used in information …

Three-way concept analysis provides a new model to make three-way decisions. Its basic
structure can be shown by the three-way concept lattices. Thus, how to construct three-way …

As one popular clustering algorithm in the last few years, spectral clustering is
advantageous over most existing clustering algorithms. Although spectral clustering can …

The incremental learning technology has been widely applied in efficient and effective data
mining with big data based on granular computing, rough sets and three-way approaches. In …