In the field of rough set, how to improve the efficiency of obtaining reduct has been paid
much attention to. One of the typical strategies is to reduce the number of comparisons …

Feature selection with rough sets aims to delete redundant conditional features from static
data by considering single type features. However, traditional feature selection methods …

In neighborhood rough set, radius is a key factor. Different radii may generate different
neighborhood relations for discriminating samples. Unfortunately, it is possible that two …

Neighborhood Covering (NC) is the union of homogeneous neighborhoods and provides a
set-level approximation of data distribution. Because of the nonparametric property and the …

In recent years, the number of review texts on online travel review sites has increased
dramatically, which has provided a novel source of data for travel research. Sentiment …

A granular structure of intuitionistic fuzzy (IF) information presents simultaneously the
similarity and diversity of samples. However, this structural representation has rarely …

Neighborhoods form a set-level approximation of data distribution for learning tasks. Due to
the advantages of data generalization and nonparametric property, neighborhood models …

Presently, attribute reduction, as one of the most important topics in the field of rough set,
has been widely explored from different perspectives. To derive the qualified reduct defined …

The Evidential K-Nearest Neighbor (EK-NN) classification rule provides a global treatment of
imperfect knowledge in class labels, but still suffers from the curse of dimensionality as well …

A covering information system as the generalization of an information system is an important
model in the field of artificial intelligence. This paper explores information structures in a …