Educational big data analytics and computational intelligence have transformed our
understanding of learning ability and computing power, catalyzing the emergence of …

Online product reviews have become increasingly important in digital consumer markets
where they play a crucial role in making purchasing decisions by most consumers …

In this paper, for the first time, a feature selection procedure is modeled as a multi-criteria
decision making (MCDM) process. This method is applied to a multi-label data and we have …

For the first time, the ensemble feature selection is modeled as a Multi-Criteria Decision-
Making (MCDM) process in this paper. For this purpose, we used the VIKOR method as a …

Feature extraction and feature selection have been regarded as two independent
dimensionality reduction methods in most of the existing literature. In this paper, we propose …

Fuzzy clustering is a classical approach to provide the soft partition of data. Although its
enhancements have been intensively explored, fuzzy clustering still suffers from the …

Recently, a new density-peak-based clustering method, called clustering with local density
peaks-based minimum spanning tree (LDP-MST), was proposed, which has several …

Clustering analysis has been widely used in statistics, machine learning, pattern recognition,
image processing, and so on. It is a great challenge for most existing clustering algorithms to …

Although k-means and its variants are known for their remarkable efficiency, they suffer from
a strong dependence on the prior knowledge of K and the assumption of a circle-like pattern …

This paper provides a short overview of space–time series clustering, which can be
generally grouped into three main categories such as: hierarchical, partitioning-based, and …