Neighborhood rough sets are widely used as an effective tool to deal with numerical data.
However, most of the existing neighborhood granulation models cannot well describe the …

It is beneficial to automate the process of deriving concept hierarchies from corpora since a
manual construction of concept hierarchies is typically a time-consuming and resource …

In this study, a granular ball based selector was developed for reducing the dimensions of
data from the perspective of attribute reduction. The granular ball theory offers a data …

In rough set based Granular Computing, neighborhood relation has been widely accepted
as one of the most popular approaches for realizing information granulation. Such approach …

The three-way classifications aim to divide the universe of objects into three disjoint regions,
ie, acceptance, rejection, and non-commitment regions. We can induce different types of …

In many real applications, the data are always collected from different types and they are
subjected to obtain partial labeling information of objects. Such data are referred to as …

Formal concept analysis (FCA) extracts interpretable rules by using implication relationships
between concepts, which is an effective method for acquiring knowledge. In this article, a …

Theories of fuzzy sets and rough sets are related and complementary methodologies to
handle uncertainty of vagueness and coarseness, respectively. Marrying both leads to the …

How to reduce the complexity of lattice construction is an important research topic in formal
concept analysis. Based on granularity tree, the relationship between the extent and the …

A rule is an effective representation of knowledge in formal concept analysis (FCA), which
can express the relations between concepts. One of the main research directions of FCA is …