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Graph-based Techniques for Topic Classification of Tweets (Técnicas basadas en grafos para la categorización de tweets por tema)

dc.contributor.authorCordobés de la Calle, Héctor 
dc.contributor.authorFernández Anta, Antonio 
dc.contributor.authorChiroque, Luis F. 
dc.contributor.authorPérez, Fernando
dc.contributor.authorRedondo, Teófilo
dc.contributor.authorSantos, Agustín 
dc.date.accessioned2021-07-13T10:08:48Z
dc.date.available2021-07-13T10:08:48Z
dc.date.issued2013-09-20
dc.identifier.urihttp://hdl.handle.net/20.500.12761/1286
dc.descriptionSEPLN 2013 – XXIX Congreso de la Sociedad Española para el Procesamiento del Lenguaje Natural, co-located with the Spanish Informatics Conference (CEDI2013 – IV Congreso Español de Informática)
dc.description.abstractTopic classification of texts is one of the most interesting challenges in Natural Language Processing (NLP). In this work we present a technique based on graph similarity to classify Twitter messages as being related to a specific topic.
dc.language.isoeng
dc.titleGraph-based Techniques for Topic Classification of Tweets (Técnicas basadas en grafos para la categorización de tweets por tema)en
dc.typeconference object
dc.conference.date18-20 September 2013
dc.conference.placeMadrid, Spain
dc.conference.titleSpanish Society for Natural Language Processing Conference (SEPLN 2013)*
dc.event.typeworkshop
dc.pres.typepaper
dc.type.hasVersionAM
dc.rights.accessRightsopen access
dc.subject.keywordTopic classification
dc.subject.keywordtext classification
dc.subject.keywordgraphs
dc.subject.keywordnatural language processing
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttp://eprints.networks.imdea.org/id/eprint/722


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