Bilingual document clustering using Translation-Independent features

dc.creatorClaudia Denicia Carral
dc.creatorManuel Montes y Gómez
dc.creatorLuis Villaseñor Pineda
dc.creatorRITA MARIANA ACEVES PEREZ
dc.date2010
dc.date.accessioned2023-07-25T16:24:01Z
dc.date.available2023-07-25T16:24:01Z
dc.identifierhttp://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1618
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7806812
dc.descriptionThis paper focuses on the task of bilingual clustering, which involves dividing a set of documents from two different languages into a set of thematically homogeneous groups. It mainly proposes a translation independent approach specially suited to deal with linguistically related languages. In particular, it proposes representing the documents by pairs of words orthographically or thematically related. The experimental evaluation in three bilingual collections and using two clustering algorithms demonstrated the appropriateness of the proposed representation, which results are comparable to those from other approaches based on complex linguistic resources such as translation machines, part-of-speech taggers, and named entity recognizers.
dc.formatapplication/pdf
dc.languageeng
dc.publisherIJCLA
dc.relationcitation:Denicia-Carral, C., et al., (2010). Bilingual document clustering using Translation-Independent features, IJCLA Vol. 1 (1-2): 217-230
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectinfo:eu-repo/classification/cti/1
dc.subjectinfo:eu-repo/classification/cti/12
dc.subjectinfo:eu-repo/classification/cti/1203
dc.subjectinfo:eu-repo/classification/cti/1203
dc.titleBilingual document clustering using Translation-Independent features
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.audiencestudents
dc.audienceresearchers
dc.audiencegeneralPublic


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