The smart city vision has driven the rapid development and advancement of interconnected
technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this …

Due to its ability to combine multiple base clusterings into a probably better and more robust
clustering, the ensemble clustering technique has been attracting increasing attention in …

Ensemble clustering has been a popular research topic in data mining and machine
learning. Despite its significant progress in recent years, there are still two challenging …

In recent years, combining multiple sources or views of datasets for data clustering has been
a popular practice for improving clustering accuracy. As different views are different …

The density peak clustering algorithm treats local density peaks as cluster centers, and
groups non-center data points by assuming that one data point and its nearest higher …

In this paper, we make an extension of K-means for the clustering of multiple means. The
popular K-means clustering uses only one center to model each class of data. However, the …

In this paper, we propose a new ensemble clustering approach termed ensemble clustering
using factor graph (ECFG). Compared to the existing approaches, our approach has three …

The availability of many heterogeneous but related views of data has arisen in numerous
clustering problems. Different views encode distinct representations of the same data, which …

Density peaks is a popular clustering algorithm, used for many different applications,
especially for non-spherical data. Although powerful, its use is limited by quadratic time …

Multi-view clustering is a hot research topic due to the urgent need for analyzing a vast
amount of heterogeneous data. Although many multi-view clustering methods have been …