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Learning IS-A relations from specialized-domain texts with co-occurrence measures

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Learning IS-A relations from specialized-domain texts with co-occurrence measures

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dc.contributor.author Ureña Gómez-Moreno, Pedro es_ES
dc.date.accessioned 2018-09-03T12:31:31Z
dc.date.available 2018-09-03T12:31:31Z
dc.date.issued 2018-07-12
dc.identifier.uri http://hdl.handle.net/10251/106475
dc.description.abstract [EN] Ontology enrichment is a classification problem in which an algorithm categorizes an input conceptual unit in the corresponding node in a target ontology. Conceptual enrichment is of great importance both to Knowledge Engineering and Natural Language Processing, because it helps maximize the efficacy of intelligent systems, making them more adaptable to scenarios where information is produced by means of language. Following previous research on distributional semantics, this paper presents a case study of ontology enrichment using a feature-extraction method which relies on collocational information from corpora. The major advantage of this method is that it can help locate an input unit within its corresponding superordinate node in a taxonomy using a relatively small number of lexical features. In order to evaluate the proposed framework, this paper presents an experiment consisting of the automatic classification of a chemical substance in a taxonomy of toxicology. es_ES
dc.description.sponsorship This article is based on research carried out within the framework of the Project FFI2014-53788-C3-1-P, which is funded by the Spanish Ministry of Economy and Competitiveness, and entitled: Development of a virtual laboratory for natural language processing from a functional paradigm. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València
dc.relation.ispartof Journal of Computer-Assisted Linguistic Research
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Ontology learning es_ES
dc.subject Ontology enrichment es_ES
dc.subject Taxonomy es_ES
dc.subject Corpus linguistics es_ES
dc.subject Co-occurrence es_ES
dc.title Learning IS-A relations from specialized-domain texts with co-occurrence measures es_ES
dc.type Artículo es_ES
dc.date.updated 2018-09-03T12:16:51Z
dc.identifier.doi 10.4995/jclr.2018.9916
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//FFI2014-53788-C3-1-P/ES/DESARROLLO DE UN LABORATORIO VIRTUAL PARA EL PROCESAMIENTO COMPUTACIONAL DEL LENGUAJE NATURAL DESDE UN PARADIGMA FUNCIONAL/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Ureña Gómez-Moreno, P. (2018). Learning IS-A relations from specialized-domain texts with co-occurrence measures. Journal of Computer-Assisted Linguistic Research. 2(1):21-38. https://doi.org/10.4995/jclr.2018.9916 es_ES
dc.description.accrualMethod SWORD es_ES
dc.relation.publisherversion https://doi.org/10.4995/jclr.2018.9916 es_ES
dc.description.upvformatpinicio 21 es_ES
dc.description.upvformatpfin 38 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2
dc.description.issue 1
dc.identifier.eissn 2530-9455
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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