In the eld of safety-critical real-time systems the development of distributed applications for fault tolerance reasons is a common practice. Hereby the whole application is divid...
We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...
We present a rigorous framework, based on optimization, for evaluating data mining operations such as associations and clustering, in terms of their utility in decisionmaking. Thi...
Jon M. Kleinberg, Christos H. Papadimitriou, Prabh...
The major limitation in bilingual latent semantic analysis (bLSA) is the requirement of parallel training corpora. Motivated by semi-supervised learning, we propose a clusterbased...
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by...