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A syntactic approach for opinion mining on Spanish reviews
dc.contributor.author | Vilares, David | |
dc.contributor.author | Alonso, Miguel A. | |
dc.contributor.author | Gómez-Rodríguez, Carlos | |
dc.date.accessioned | 2024-01-18T16:29:09Z | |
dc.date.available | 2024-01-18T16:29:09Z | |
dc.date.issued | 2015-01 | |
dc.identifier.citation | Vilares, D., Alonso, M., & Gómez-Rodríguez, C. (2015). A syntactic approach for opinion mining on Spanish reviews. Natural Language Engineering, 21(1), 139-163. doi:10.1017/S1351324913000181 | es_ES |
dc.identifier.issn | 1351-3249 | |
dc.identifier.issn | 1469-8110 | |
dc.identifier.uri | http://hdl.handle.net/2183/34989 | |
dc.description | This accepted version of the article has been published in a revised form in Natural Language Engineering, 21(1), 139-163. https://doi.org/10.1017/S1351324913000181 . This version is published under a Creative Commons CC-BY-NC-ND licence. No commercial re-distribution or re-use allowed. Derivative works cannot be distributed. © Cambridge University Press 2013 . | es_ES |
dc.description.abstract | [Abstract]: We describe an opinion mining system which classifies the polarity of Spanish texts. We propose an NLP approach that undertakes pre-processing, tokenisation and POS tagging of texts to then obtain the syntactic structure of sentences by means of a dependency parser. This structure is then used to address three of the most significant linguistic constructions for the purpose in question: intensification, subordinate adversative clauses and negation. We also propose a semi-automatic domain adaptation method to improve the accuracy of our system in specific application domains, by enriching semantic dictionaries using machine learning methods in order to adapt the semantic orientation of their words to a particular field. Experimental results are promising in both general and specific domains. | es_ES |
dc.description.sponsorship | Research reported in this paper has been partially funded by Ministerio de Economía y Competitividad and FEDER (grant TIN2010-18552-C03-02) and by Xunta de Galicia (grants CN2012/008, CN2012/319). We thank Maite Taboada for giving us access to SODictionariesV1.11Spa. | es_ES |
dc.description.sponsorship | Xunta de Galicia; CN2012/008 | es_ES |
dc.description.sponsorship | Xunta de Galicia; CN2012/319 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Cambridge University Press | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/Plan Nacional de I+D+i 2008-2011/TIN2010-18552-C03-02/ES/ANALISIS DE TEXTOS Y RECUPERACION DE INFORMACION PARA LA MINERIA DE OPINIONES: ANALISIS DE ENUNCIADOS Y EXTRACCION DE RELACIONES | es_ES |
dc.relation.isversionof | https://doi.org/10.1017/S1351324913000181 | |
dc.relation.uri | https://doi.org/10.1017/S1351324913000181 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Sentiment Analysis | es_ES |
dc.subject | Natural language processing | es_ES |
dc.subject | Opinion mining | es_ES |
dc.title | A syntactic approach for opinion mining on Spanish reviews | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Natural Language Engineering | es_ES |
UDC.volume | 21 | es_ES |
UDC.issue | 1 | es_ES |
UDC.startPage | 139 | es_ES |
UDC.endPage | 163 | es_ES |
dc.identifier.doi | 10.1017/S1351324913000181 |
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