There is an increasing demand to introduce adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational con...
Nishanth Shankaran, Xenofon D. Koutsoukos, Douglas...
Conventional clustering techniques provide a static snapshot of each vector's commitment to every group. With additive datasets, however, existing methods may not be sufficie...
To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
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...
Document clustering has been used for better document retrieval, document browsing, and text mining in digital library. In this paper, we perform a comprehensive comparison study ...