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dc.contributor.authorAlonso Berrocal, José Luis 
dc.contributor.authorFiguerola, Carlos G.
dc.contributor.authorZazo Rodríguez, Ángel Francisco 
dc.date.accessioned2016-05-03T10:13:05Z
dc.date.available2016-05-03T10:13:05Z
dc.date.issued2013-09-23
dc.identifier.citationAlonso Berrocal, J. L., Figuerola, C. G. and Zazo Rodríguez, Á. F. (2013). REINA at RepLab2013 Topic Detection Task: Community Detection. In Pamela Forner, Roberto Navigli and Dan Tufis (eds.). Working Notes for the CLEF 2013 Evaluation Labs and Workshop, Valencia, 23-26 September, 2013.es_ES
dc.identifier.urihttp://hdl.handle.net/10366/128126
dc.description.abstract[EN]Social networks have become a large repository of comments which can extract multiple information. Twitter is one of the most widespread social networks and larger and is therefore an important source for detecting states of opinion, events and happenings before even the mainstream media. Topic detection is important to discover areas of interest that arise in the tweets. We have used classical systems for a similarity matrix and we have used community detection techniques. The results have been good and allows us to study new possibilities.es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectDetección de materiases_ES
dc.subjectDetección de comunidadeses_ES
dc.titleREINA at RepLab2013 Topic Detection Task: Community Detectiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported