Ponencia
Improving Spanish Polarity Classification Combining Different Linguistic Resources
Autor/es | Martínez Cámara, Eugenio
Cruz Mata, Fermín Molina González, M. Dolores Martín Valdivia, M. Teresa Ortega Rodríguez, Francisco Javier Ureña López, L. Alfonso |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2015 |
Fecha de depósito | 2022-03-10 |
Publicado en |
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ISBN/ISSN | 978-3-319-19580-3 0302-9743 |
Resumen | Sentiment analysis is a challenging task which is attracting
the attention of researchers. However, most of work is only focused on
English documents, perhaps due to the lack of linguistic resources for
other languages. ... Sentiment analysis is a challenging task which is attracting the attention of researchers. However, most of work is only focused on English documents, perhaps due to the lack of linguistic resources for other languages. In this paper, we present several Spanish opinion mining resources in order to develop a polarity classification system. In addition, we propose the combination of different features extracted from each resource in order to train a classifier over two different opinion corpora. We prove that the integration of knowledge from several resources can improve the final Spanish polarity classification system. The good results encourage us to continue developing sentiment resources for Spanish, and studying the combination of features extracted from different resources |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Junta de Andalucía Universidad de Jaén |
Identificador del proyecto | TIN2012-38536-C03-0
P11-TIC-7684 CEATIC-2013-01 |
Cita | Martínez Cámara, E., Cruz Mata, F., Molina González, M.D., Martín Valdivia, M.T., Ortega Rodríguez, F.J. y Ureña López, L.A. (2015). Improving Spanish Polarity Classification Combining Different Linguistic Resources. En NLDB 2015: 20th International Conference on Applications of Natural Language to Information Systems (234-245), Passau, Germany: Springer. |
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