We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
This paper proposes a demo of the TopX search engine, an extensive framework for unified indexing, querying, and ranking of large collections of unstructured, semistructured, and ...
Modeling the semantics of business services and their corresponding messages using ontologies enables flexible integration that is more adaptive to business-driven change. In thi...
Tomas Vitvar, Matthew Moran, Maciej Zaremba, Armin...
Abstract. We provide an interactive method for knowledge acquisition combining approaches from description logic and formal concept analysis. Based on present data, hypothetical ru...
The aim of this paper is to propose a service oriented decision support system based on an ontology-driven uncertainty model (OntoBayes). OntoBayes consists of knowledge and decis...