Discovering Non-taxonomic Relations from the Web

Ontology Learning Part One - On Discovering Taxonomic Relations from the Web

Discovery of Non-Taxonomic Concept Pairs from Unstructured Text in Support of Ontology Learning

Ontology consists of concepts, taxonomic relations and non-taxonomic relations. The majority of the ontology learning tools focus on discovering concepts and taxonomic relations. Very little effort has been put on discovering non-taxonomic relations. In this paper, we present a concept correlation search framework to discover non-taxonomic concept pairs from unstructured text. Our framework fea...

On Discovering Taxonomic Relations from the Web

Alexander Maedche, Viktor Pekar, and Steffen Staab 1 FZI University of Karlsruhe Germany http://www.fzi.de/wim 2 Bashkir State University Okt.Revolutsii 3a Ufa, Russia, 450000 [email protected] 3 Institute AIFB University of Karlsruhe Germany http://www.aifb.unikarlsruhe.de/WBS & Learning Lab Lower Saxony Hannover, Germany http://www.learninglab.de & Ontoprise GmbH Karlsruhe, Germany http://www....

Non-taxonomic Relations in Semantic Service Discovery and Composition

Existing approaches for semantic web service discovery are often based on subsumption reasoning, i.e. on evaluating taxonomic relations between the ontology concepts used in the service descriptions. If these concepts are not related taxonomically, no match is found. In this paper we present an approach that recognizes the importance of non-taxonomic relations. To increase recall, it uses opera...

Discovering Conceptual Relations from Text

Non-taxonomic relations between concepts appear as a major building block in common ontology definitions. In fact, their definition consumes much of the time needed for engineering an ontology. We here describe a new approach to discover non-taxonomic conceptual relations from text building on shallow text processing techniques. We use a generalized association rule algorithm that does not only...