We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
Despite outstanding successes of the state-of-the-art clustering algorithms, many of them still suffer from shortcomings. Mainly, these algorithms do not capture coherency and homo...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...
A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
Many practical applications of clustering involve data collected over time. In these applications, evolutionary clustering can be applied to the data to track changes in clusters ...