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Cross-domain polarity classification using a knowledge-enhanced meta-classifier

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Cross-domain polarity classification using a knowledge-enhanced meta-classifier

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dc.contributor.author Franco-Salvador, Marc es_ES
dc.contributor.author Cruz, Fermín L. es_ES
dc.contributor.author Troyano Jiménez, José Antonio es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.date.accessioned 2016-05-11T12:41:10Z
dc.date.available 2016-05-11T12:41:10Z
dc.date.issued 2015-09
dc.identifier.issn 0950-7051
dc.identifier.uri http://hdl.handle.net/10251/63907
dc.description "NOTICE: this is the author’s version of a work that was accepted for publication in Knowledge-Based Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in KNOWLEDGE-BASED SYSTEMS [Volume 86, September 2015, Pages 46–56] DOI http://dx.doi.org/10.1016/j.knosys.2015.05.020 es_ES
dc.description.abstract In this paper, we propose the use of meta-learning to combine and enrich those approaches by adding also other knowledge-based features. In addition to the aforementioned classical approaches, our system uses the BabelNet multilingual semantic network to generate features derived from word sense disambiguation and vocabulary expansion. Experimental results show state-of-theart performance on single and cross-domain polarity classification. es_ES
dc.description.sponsorship This research has been carried out in the framework of the European Commission WIQ-EI IRSES (No. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) projects. This research is partially funded by the national project ACOGEUS (TIN2012-38536-C03-02) and the regional project AORESCU (P11-TIC-7684 MO). We thank Juan M. Cotelo and Luis A. Leiva for their support and comments. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation European Commission WIQ-EI IRSES (No. 269180) es_ES
dc.relation.ispartof Knowledge-Based Systems es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Sentiment analysis es_ES
dc.subject Cross-domain polarity classification es_ES
dc.subject Meta-learning es_ES
dc.subject Word sense disambiguation es_ES
dc.subject Semantic network es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Cross-domain polarity classification using a knowledge-enhanced meta-classifier es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.knosys.2015.05.020
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-38603-C02-01/ES/DIANA-APPLICATIONS: FINDING HIDDEN KNOWLEDGE IN TEXTS: APPLICATIONS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-38536-C03-02/ES/ANALISIS DE CONTENIDOS GENERADOS POR USUARIOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Junta de Andalucía//P11-TIC-7684 MO/ES/AORESCU Project/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Franco-Salvador, M.; Cruz, FL.; Troyano Jiménez, JA.; Rosso, P. (2015). Cross-domain polarity classification using a knowledge-enhanced meta-classifier. Knowledge-Based Systems. 86:46-56. https://doi.org/10.1016/j.knosys.2015.05.020 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.knosys.2015.05.020 es_ES
dc.description.upvformatpinicio 46 es_ES
dc.description.upvformatpfin 56 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 86 es_ES
dc.relation.senia 302673 es_ES
dc.contributor.funder Junta de Andalucía es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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