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dc.contributor.authorAgirre, Eneko
dc.contributor.authorRigau Claramunt, German
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2016-02-05T10:58:03Z
dc.date.available2016-02-05T10:58:03Z
dc.date.issued1996-01
dc.identifier.citationAgirre, E., Rigau, G. "Word sense disambiguation using conceptual density". 1996.
dc.identifier.urihttp://hdl.handle.net/2117/82607
dc.description.abstractThis paper presents a method for the resolution of lexical ambiguity and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed for this purpose. This fully automatic method requires no hand coding of lexical entries, hand tagging of text nor any kind of training process. The results of the experiment have been automatically evaluated against SemCor, the sense-tagged version of the Brown Corpus.
dc.format.extent13 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.otherSemCor
dc.subject.otherBrown Corpus
dc.subject.otherWord sense disambiguation
dc.titleWord sense disambiguation using conceptual density
dc.typeExternal research report
dc.rights.accessOpen Access
local.identifier.drac1847825
dc.description.versionPostprint (author's final draft)
local.citation.authorAgirre, E.; Rigau, G.


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