Clustering is an unsupervised learning technology, and it groups information (observations
or datasets) according to similarity measures. Developing clustering algorithms is a hot topic …

The breakthrough impact of new-born companies over the last years brought to the definition
of Big Bang Disruption, a new kind of innovation that relies on an unencumbered …

Clustering algorithm plays a vital role in organizing large amount of information into small
number of clusters which provides some meaningful information. Clustering is a process of …

Although attempts have been made to solve the problem of clustering categorical data via
cluster ensembles, with the results being competitive to conventional algorithms, it is …

Unsupervised hierarchical clustering process is a mathematical model or exploratory tool
aims to provide the easiest way to categorize the distinct groups over the large volume of …

Density peak clustering algorithms and their variants have achieved promising results in
many fields over the last few years. However, most of these algorithms parameters requiring …

Similarity or distance between two objects plays a fundamental role in many data mining
tasks like classification and clustering. Categorical data, unlike numeric data, conceptually is …

Clustering is an unsupervised learning technique that discovers intrinsic groups based on
proximity between data points. Therefore, the performance of clustering techniques mainly …

Plentiful, complex, and dynamic data make understanding the state of an enterprise network
difficult. Although visualization can help analysts understand baseline behaviors in network …

Categorical data clustering is a difficult and challenging task due to the special characteristic
of categorical attributes: no natural order. Thus, this study aims to propose a two-stage …