Human-Inspired Computing and Its Applications: 13th Mexican by Alexander Gelbukh, Félix Castro Espinoza, Sofía N.

By Alexander Gelbukh, Félix Castro Espinoza, Sofía N. Galicia-Haro (eds.)

The two-volume set LNAI 8856 and LNAI 8857 constitutes the court cases of the thirteenth Mexican overseas convention on synthetic Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. the whole of 87 papers plus 1 invited speak awarded in those lawsuits have been rigorously reviewed and chosen from 348 submissions. the 1st quantity bargains with advances in human-inspired computing and its purposes. It comprises forty four papers established into seven sections: ordinary language processing, average language processing functions, opinion mining, sentiment research, and social community purposes, machine imaginative and prescient, picture processing, common sense, reasoning, and multi-agent platforms, and clever tutoring structures. the second one quantity bargains with advances in nature-inspired computation and desktop studying and includes additionally forty four papers dependent into 8 sections: genetic and evolutionary algorithms, neural networks, computing device studying, laptop studying purposes to audio and textual content, information mining, fuzzy common sense, robotics, making plans, and scheduling, and biomedical applications.

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Additional info for Human-Inspired Computing and Its Applications: 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, Tuxtla Gutiérrez, Mexico, November 16-22, 2014. Proceedings, Part I

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Accurate unlexicalized parsing. In: Proceedings of the 41st Annual Meeting on Association for Computational Linguistics, vol. 1, pp. 423–430. Association for Computational Linguistics (2003) 10. : Non-continuous syntactic n-grams. Polibits 48, 67–75 (2013) 11. : Syntactic dependency based n-grams in rule based automatic english as second language grammar correction. International Journal of Computational Linguistics and Applications 4(2), 169–188 (2013) 12. : Syntactic n-grams as machine learning features for natural language processing.

Information about case of nouns that controlled by verb through specified preposition. Authors review previous works and their limitations like insufficient dictionary size that prevents to use such dictionaries in a computer system. Existing treebanks of Russian language also have insufficient corpus size for automatic generation of a complete verbal subordination dictionary. There is a difference with previous woks that ambiguous part of text is not processed at all. Authors note that ambiguity in Russian language has a big difference from ambiguity in English.

Analysis of definitions of verbs in an explanatory dictionary for automatic extraction of actants based on detection of patterns. , Li, H. ) NLDB 2010. LNCS, vol. 6177, pp. 233–239. Springer, Heidelberg (2010) 3. : Lexicon and grammar in bulgarian framenet. In: LREC (2010) 4. : Syntactic annotations for the google books ngram corpus. In: Proceedings of the ACL 2012 System Demonstrations, pp. 169–174. Association for Computational Linguistics (2012) 5. : Ruthes linguistic ontology vs. russian wordnets.

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