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...
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...
Radix-r modulo rn multipliers and adders are introduced in this paper. The proposed architectures are shown to require several times less area than previously reported architectur...
: In many application areas like e-science and data-warehousing detailed information about the origin of data is required. This kind of information is often referred to as data pro...
Content-based retrieval (CBIR) methods in medical databases have been designed to support specific tasks, such as retrieval of digital mammograms or 3D MRI images. These methods c...