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dc.contributor.author | Stuart, Keith Douglas Charles | es_ES |
dc.contributor.author | Majewski, Maciej | es_ES |
dc.contributor.author | Botella Trelis, Ana Paloma | |
dc.date.accessioned | 2015-06-02T16:23:09Z | |
dc.date.available | 2015-06-02T16:23:09Z | |
dc.date.issued | 2011 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/10251/51150 | |
dc.description.abstract | The paper describes the application of hybrid probabilistic neural networks for corpus analysis which consists of intelligent semantic based methods of analysis and recognition of word clusters and their meaning. The task of analyzing a corpus of academic articles was resolved with hybrid probabilistic neural networks and developed word clusters. The created prototypes of word clusters provide the probabilistic neural networks with possibilities of recognizing corpus clusters. The established corpus comprises 1376 articles, from specialist leading SCI-indexed journals, and provides representative samples of the language of science and technology. In this paper, a review of selected issues is carried out with regards to computational approaches to language modelling as well as semantic patterns of language. The paper features semanticbased recognition algorithms of word clusters of similar meanings but different lexico-grammatical patterns from the established corpus using multilayer neural networks. The paper also presents experimental results of word cluster semantic-based recognition in the context of phrase meaning analysis. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Springer Verlag (Germany) | es_ES |
dc.relation.ispartof | Lecture Notes in Computer Science | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | corpus analysis | es_ES |
dc.subject | artificial intelligence | es_ES |
dc.subject | probabilistic neural | es_ES |
dc.subject | networks | es_ES |
dc.subject | semantic networks | es_ES |
dc.subject | phrase meaning analysis | es_ES |
dc.subject | natural language processing | es_ES |
dc.subject | applied computational linguistics | es_ES |
dc.subject.classification | FILOLOGIA INGLESA | es_ES |
dc.title | Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1007/978-3-642-21105-8_11 | |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Lingüística Aplicada - Departament de Lingüística Aplicada | es_ES |
dc.description.bibliographicCitation | Stuart, KDC.; Majewski, M.; Botella Trelis, AP. (2011). Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks. Lecture Notes in Computer Science. 6675:83-92. doi:10.1007/978-3-642-21105-8_11 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-642-21105-8_11 | es_ES |
dc.description.upvformatpinicio | 83 | es_ES |
dc.description.upvformatpfin | 92 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 6675 | es_ES |
dc.relation.senia | 215551 | |
dc.description.references | Biber, D.: Variation across speech and writing. Cambridge University Press, Cambridge (1988) | es_ES |
dc.description.references | Biber, D.: Using register-diversified corpora for general language studies. Computational Linguistics 19(2), 219–241 (1993) | es_ES |
dc.description.references | Biber, D., Conrad, S., Reppen, R.: Corpus linguistics: Investigating language structure and use. Cambridge University Press, Cambridge (1998) | es_ES |
dc.description.references | Cacoullous, R.: Estimation of a probability density. Annals of the Institute of Statistical Mathematics (Tokyo) 18(2), 179–189 (1966) | es_ES |
dc.description.references | Carter, R., Hughes, R., McCarthy, M.: Exploring grammar in context. Cambridge University Press, Cambridge (2000) | es_ES |
dc.description.references | Jurafsky, D.: A probabilistic model of lexical and syntactic access and disambiguation. Cognitive Science 20(2), 137–194 (1996) | es_ES |
dc.description.references | Jurafsky, D., Martin, J.H.: Speech and language processing: An introduction to natural language processing. In: Speech Recognition, and Computational Linguistics. Prentice-Hall, New Jersey (2000) | es_ES |
dc.description.references | Kacalak, W., Stuart, K., Majewski, M.: Intelligent natural language processing. In: Jiao, L., Wang, L., Gao, X.-b., Liu, J., Wu, F. (eds.) ICNC 2006. LNCS, vol. 4221, pp. 584–587. Springer, Heidelberg (2006) | es_ES |
dc.description.references | Kacalak, W., Stuart, K., Majewski, M.: Selected problems of intelligent handwriting recognition. Advances in Soft Computing 41, 298–305 (2007) | es_ES |
dc.description.references | Kennedy, G.: An introduction to corpus linguistics. Longman, London (1998) | es_ES |
dc.description.references | Lapata, M., Keller, F., Schulte, S.: Verb frame frequency as a predictor of verb bias. Journal of Psycholinguistic Research 30(4), 419–435 (2001) | es_ES |
dc.description.references | Manning, C., Schtze, H.: Foundations of statistical natural language processing. MIT Press, Cambridge (1999) | es_ES |
dc.description.references | Murthy, V.K.: Estimation of a probability density. The Annals of Mathematical Statistics 36(3), 1027–1031 (1965) | es_ES |
dc.description.references | Parzen, E.: On estimation of a probability density function and mode. The Annals of Mathematical Statistics 33(3), 1065–1076 (1962) | es_ES |
dc.description.references | Roland, D., Elman, J.L., Ferreira, V.S.: Why is that? Structural prediction and ambiguity resolution in a very large corpus of English sentences. Cognition 98(3), 245–272 (2006) | es_ES |
dc.description.references | Sampson, G.: English for the computer. Oxford University Press, Oxford (1995) | es_ES |
dc.description.references | Sinclair, J.: Corpus, Concordance, Collocation. Oxford University Press, Oxford (1991) | es_ES |
dc.description.references | Specht, D.F.: Probabilistic neural networks. Neural Networks 3(1), 109–118 (1990) | es_ES |
dc.description.references | Specht, D.F.: A general regression neural network. IEEE Transactions on Neural Networks 2(6), 568–576 (1991) | es_ES |
dc.description.references | Specht, D.F.: Enhancements to probabilistic neural networks. In: Proceedings of the IEEE International Joint Conference on Neural Networks, Baltimore Maryland USA, vol. 1, pp. 761–768 (1992) | es_ES |
dc.description.references | Specht, D.F., Romsdahl, H.: Experience with adaptive probabilistic neural networks and adaptivegeneral regression neural networks. In: IEEE World Congress on Computational Intelligence, IEEE International Conference on Neural Networks, Orlando Florida USA, vol. 2, pp. 1203–1208 (1994) | es_ES |
dc.description.references | Stuart, K., Majewski, M.: Selected problems of knowledge discovery using artificial neural networks. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds.) ISNN 2007. LNCS, vol. 4493, pp. 1049–1057. Springer, Heidelberg (2007) | es_ES |
dc.description.references | Stuart, K., Majewski, M.: A new method for intelligent knowledge discovery. Advances in Soft Computing 42, 721–729 (2007) | es_ES |
dc.description.references | Stuart, K., Majewski, M.: Artificial creativity in linguistics using evolvable fuzzy neural networks. In: Hornby, G.S., Sekanina, L., Haddow, P.C. (eds.) ICES 2008. LNCS, vol. 5216, pp. 437–442. Springer, Heidelberg (2008) | es_ES |
dc.description.references | Stuart, K., Majewski, M.: Evolvable neuro-fuzzy system for artificial creativity in linguistics. In: Huang, D.-S., Wunsch II, D.C., Levine, D.S., Jo, K.-H. (eds.) ICIC 2008. LNCS (LNAI), vol. 5227, pp. 46–53. Springer, Heidelberg (2008) | es_ES |
dc.description.references | Stuart, K.D., Majewski, M., Trelis, A.B.: Selected problems of intelligent corpus analysis through probabilistic neural networks. In: Zhang, L., Lu, B.-L., Kwok, J. (eds.) ISNN 2010. LNCS, vol. 6064, pp. 268–275. Springer, Heidelberg (2010) | es_ES |