Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

Density peak clustering (DPC) algorithm has become a well-known clustering method
during the last decade, The research communities believe that DPC is a powerful tool …

Generally, data is available abundantly in unlabeled form, and its annotation requires some
cost. The labeling, as well as learning cost, can be minimized by learning with the minimum …

Recently, the advancement of cognitive computing and three-way decisions has enabled in-
depth sequential pattern understanding through temporal association analysis. The main …

The scale of the radius for constructing neighborhood relation has a great effect on the
results of neighborhood rough sets and corresponding measures. A very small radius …

Energy load balancing is an essential issue in designing wireless sensor networks (WSNs).
Clustering techniques are utilized as energy-efficient methods to balance the network …

Recommender systems (RSs) are effective technologies and tools used to deal with the
problems of information overload, and have been developed rapidly in nearly two decades …

Given a large unlabeled set of complex data, how to efficiently and effectively group them
into clusters remains a challenging problem. Density peaks clustering (DPC) algorithm is an …

A fundamental notion of granular computing is a multilevel granular structure in which
different levels are characterized by different degrees of abstraction and details. By making …

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 …