2000 · 167 citations · 9 references
ComputingComputer ScienceComputational LinguisticsKnowledge RepresentationNatural Language ProcessingConcept ExtractionFormal OntologyKnowledge AcquisitionKnowledge ExtractionOntology EngineeringTaxonomyAssociation Rule LearningAssociation Rule MiningConceptual RelationsOntologiesOntology AcquisitionTaxonomic RelationsTaxonomy Induction
Ontologies have become an important means for structuring information and information systems and, hence, important in knowledge as well as in software engineering. However, there remains the problem of engineering large and adequate ontologies within short time frames in order to keep costs low. For this purpose, eorts have been made to facilitate the ontology engineering process, in particular the acquisition of ontologies from domain texts. We present a general architecture for discovering conceptual structures and engineering ontologies. Based on the architecture we propose a new approach to extend current approaches, who mostly focus on the semi-automatic acquisition of taxonomies, by the discovery of non-taxonomic conceptual relations. We use a generalized association rule algorithm that does not only detect relations between concepts, but also determines the appropriate level of abstraction at which to dene relations. 1 Introduction Ontologies 1 have shown their usefulness...
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