- -

Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks

Show simple item record

Files in this item

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


This item appears in the following Collection(s)

Show simple item record