Given a collection of complex, time-stamped events, how do we find patterns and anomalies? Events could be meetings with one or more persons with one or more agenda items at zero ...
Hanghang Tong, Yasushi Sakurai, Tina Eliassi-Rad, ...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
—This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performa...