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Unsupervised ontology acquisition from plain texts: the OntoGain System

Petrakis Evripidis, Euthymios Drymonas, Zervanou Kalliopi

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URIhttp://purl.tuc.gr/dl/dias/355EEAFB-C66F-4303-A0D7-6407DF7B73A6-
Identifierhttps://doi.org/10.1007/978-3-642-13881-2_29-
Languageen-
TitleUnsupervised ontology acquisition from plain texts: the OntoGain Systemen
CreatorPetrakis Evripidisen
CreatorΠετρακης Ευριπιδηςel
CreatorEuthymios Drymonasen
Creatoren
CreatorZervanou Kalliopien
CreatorΖερβανου Καλλιοπηel
PublisherSpringer Verlagen
Content SummaryWe propose OntoGain, a system for unsupervised ontology acquisition from unstructured text which relies on multi-word term extraction. For the acquisition of taxonomic relations, we exploit inherent multi-word terms’ lexical information in a comparative implementation of agglomerative hierarchical clustering and formal concept analysis methods. For the detection of non-taxonomic relations, we comparatively investigate in OntoGain an association rules based algorithm and a probabilistic algorithm. The OntoGain system allows for transformation of the derived ontology into standard OWL statements. OntoGain results are compared to both hand-crafted ontologies, as well as to a state-of-the art system, in two different domains: the medical and computer science domains.en
Type of ItemΠερίληψη Δημοσίευσης σε Συνέδριοel
Type of ItemConference Paper Abstracten
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-01-
Date of Publication2010-
Bibliographic CitationEuthymis Drymonas, Kalliope Zervanou, Euripides G.M. Petrakis, "Unsupervised Ontology Acquisition from Plain Texts: the OntoGain System", in 14th Intern. Conference Applications of Natural Language to Information Systems (NLDB'2010), 2010, pp. 277-287. doi:10.1007/978-3-642-13881-2_29en

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