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Knowledge-based rules for the extraction of complex, fine-grained locative references from tweets

dc.contributor.authorFernández-Martínez, Nicolás José
dc.date.accessioned2025-01-30T07:22:48Z
dc.date.available2025-01-30T07:22:48Z
dc.date.issued2020-07-14
dc.description.abstractThe automatic analysis of user-generated text content from social media involves the challenge of extracting the locative references mentioned in microtexts, so that their geographic coordinates can be identified and the locations can be pinpointed on a map in geolocation systems. The goal of this article is to describe a knowledge-based model that captures a wide variety of locative references, ranging from geopolitical entities and natural landforms to points of interest and traffic ways, from English and Spanish tweets.es_ES
dc.identifier.citationFernández-Martínez, N. J., & Periñán-Pascual, C. (2020). Knowledge-based rules for the extraction of complex, fine-grained locative references from tweets. Revista Electronica de Linguistica Aplicada, 19(1), 136–163.es_ES
dc.identifier.issn1885-9089es_ES
dc.identifier.urihttps://hdl.handle.net/10953/4546
dc.language.isoenges_ES
dc.publisherAsociacion Espanola de Linguistica Aplicadaes_ES
dc.relation.ispartofRAEL-REVISTA ELECTRONICA DE LINGUISTICA APLICADA [2020]; [19(1)]; [136-163]es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectlocation detectiones_ES
dc.subjectlocation extractiones_ES
dc.subjectgeolocationes_ES
dc.subjectnamed entity recognitiones_ES
dc.titleKnowledge-based rules for the extraction of complex, fine-grained locative references from tweetses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES

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