Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
In this paper, we consider a sentiment regression problem: summarizing the overall sentiment of a review with a real-valued score. Empirical results on a set of labeled reviews sh...
— We describe a model-driven translation approach between Semantic Web Service based business process models in the context of the SUPER project. In SUPER we provide a set of bus...
The realization of the Semantic Web requires the widespread availability of semantic annotations for existing and new documents on the Web. Semantic annotations are to tag ontolog...
Abstract. Much research has focused on the problem of knowledge accessibility, sharing and reuse. Specific languages (e.g. KIF, CG, RDF) and ontologies have been proposed. Common c...