The choice of a good clustering algorithm is vital in many tasks to optimize results. Nowadays, the most used algorithms use only one strategy to find and form the clusters of data, which can limit the effectiveness of the ...

The structure and the kinetics of formation of APTS/GPTS-derived organic/inorganic hybrids were studied in situ by small-angle-X-ray scattering. The data were interpreted in terms of a process of primary particles formation ...

The structure and the kinetics of formation of APTS/GPTS-derived organic/inorganic hybrids were studied in situ by small-angle-X-ray scattering. The data were interpreted in terms of a process of primary particles formation ...

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the ...

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the ...

An integrated framework for density-based cluster analysis, outlier detection, and data visualization is introduced in this article. The main module consists of an algorithm to compute hierarchical estimates of the level ...

Spatial clustering has been widely studied due to its application in several areas. However, the algorithms of such technique still need to overcome several challenges to achieve satisfactory results on a timely basis. ...

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be ...

How can we retrieve meaningful information from a large and sparse graph?. Traditional approaches focus on generic clustering techniques and discovering dense cumulus in a network graph, however, they tend to omit interesting ...