Classification of opinions in cross domains involving emotive values

Author:

Guzmán-Cabrera Rafael1,Sánchez Belém Priego2,Mukhopadhyay T. Prasad1,García J.M. Lozano1,Cordova-Fraga T.3

Affiliation:

1. DICIS, Universidad de Guanajuato, GTO, Mexico

2. Department of Systems, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, CDMX, Mexico

3. DCI, Universidad de Guanajuato Campus León, GTO, Mexico

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference40 articles.

1. Blitzer J. , Dredze M. and Pereira F. , Biographies, Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification, In Proceedings of the Association for Computational Linguistics (ACL), 2007.

2. A training algorithm for optimal margin classifiers;Boser;Fifth ACM Workshop on Computational Learning Theory (COLT),1992

3. Chickering D.M. , Heckerman D. and Meek C. , A bayesian approach to learning bayesian networks with local structure, In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, UAI’97, San Francisco, CA, USA, 1997, pp. 80–89. Morgan Kaufmann Publishers Inc.

4. Colmenares G. , Máquinas de vectores de soporte, Instituto de Investigaciones Económicas y Sociales (2009).

5. Díaz Galiano M. , M.R.A. and Martín Valdivia T., Mejora de los sistemas multimodales mediante el uso de ganancia de información, Sociedad Española para el Procesamiento de Lenguaje Natural, 2007.

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