The concept of three-way decision, interpreted and described as thinking, problem solving,
and information processing in “threes”, has been widely studied and applied in machine …

A theory of three-way decision is about thinking, problem-solving, and computing in threes
or through triads. In this paper, we review fifteen years of research on three-way decision by …

In recent years, multi-view clustering algorithms have shown promising performance by
combining multiple sources or views of datasets. A problem that has not been addressed …

Many existing clustering methods produce clusters with clear and sharp boundaries, which
does not truly reflect the fact that a cluster may not necessarily have a well-defined boundary …

Density peaks clustering (DPC) algorithm is an efficient and simple clustering method
attracting the attention of many researchers. However, its strategy of assigning each non …

Clustering, as an unsupervised data mining technique, allows us to classify similar objects
into the same cluster according to certain criteria. It helps us identify patterns between …

As digitalization advances and societal patterns evolve, an increasing number of experts are
becoming integral to the decision-making process. The realm of large-scale group decision …

The explainable human–computer interaction (HCI) is about designing approaches capable
of using cognitive characteristics like humans. One such characteristic is human vision and …

In this paper, a parallel deep learning-based community detection method in large complex
networks (CNs) is proposed. First, a CN partitioning method is employed to divide the CN …

The traditional k-means, which unambiguously assigns an object precisely to a single
cluster with crisp boundary, does not adequately show the fact that a cluster may not have a …