dc.creatorBotero S.W.
dc.creatorRicarte I.L.M.
dc.date2010
dc.date2015-06-26T12:41:51Z
dc.date2015-11-26T15:30:02Z
dc.date2015-06-26T12:41:51Z
dc.date2015-11-26T15:30:02Z
dc.date.accessioned2018-03-28T22:38:34Z
dc.date.available2018-03-28T22:38:34Z
dc.identifier9780769539454
dc.identifierStil 2009 - 2009 7th Brazilian Symposium In Information And Human Language Technology. , v. , n. , p. 17 - 26, 2010.
dc.identifier
dc.identifier10.1109/STIL.2009.18
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-77955965534&partnerID=40&md5=654f323acc63d765a56463edd87b91ff
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/91481
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/91481
dc.identifier2-s2.0-77955965534
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1261906
dc.descriptionOntologies are important to organize and describe information, but are hard to create and maintain, which motivates the development of tools to help in this task. This article presents a strategy to extract, from a corpora of documents in a given domain, semantic elements expressing proximity relations between terms and concepts to help the construction of domain ontologies. The technique presented here, ACT, is based on linguistic processing, machine learning, and biclustering. Results show that concepts obtained by ACT are at least as good as those from similar techniques, such as LSI and NMF. In relation to those techniques, it additionally has the advantage of allowing the supervision by a domain expert. © 2009 IEEE.
dc.description
dc.description
dc.description17
dc.description26
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dc.languagept
dc.publisher
dc.relationSTIL 2009 - 2009 7th Brazilian Symposium in Information and Human Language Technology
dc.rightsfechado
dc.sourceScopus
dc.titleSemantic Relation Extraction By Analysis Of Terms Correlation In Documents
dc.typeActas de congresos


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