— Recently several algorithms for clustering large data sets or streaming data sets have been proposed. Most of them address the crisp case of clustering, which cannot be easily ...
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...
Leximancer is a software system for performing conceptual analysis of text data in a largely language independent manner. The system is modelled on Content Analysis and provides u...
In this paper, we present Spade - the System S declarative stream processing engine. System S is a large-scale, distributed data stream processing middleware under development at ...