By Alexander Gelbukh, Félix Castro Espinoza, Sofía N. Galicia-Haro (eds.)
The two-volume set LNAI 8856 and LNAI 8857 constitutes the complaints of the thirteenth Mexican foreign convention on synthetic Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. the complete of 87 papers plus 1 invited speak provided in those court cases have been rigorously reviewed and chosen from 348 submissions. the 1st quantity bargains with advances in human-inspired computing and its purposes. It includes forty four papers based into seven sections: common language processing, normal language processing functions, opinion mining, sentiment research, and social community functions, laptop imaginative and prescient, snapshot processing, good judgment, reasoning, and multi-agent platforms, and clever tutoring platforms. the second one quantity offers with advances in nature-inspired computation and desktop studying and comprises additionally forty four papers based into 8 sections: genetic and evolutionary algorithms, neural networks, computer studying, laptop studying functions to audio and textual content, facts mining, fuzzy good judgment, 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
A more general idea consists in extending the concept of syntactic n-grams so that it includes the bifurcations in the syntactic tree [10,11]. In this way, syntactic n-grams represent the complete set of relations contained in the syntactic tree. The complete syntactic n-grams (continuous sn-grams, sn-grams with bifurcations) are obtained from the syntactic tree as subtrees, when the size of the subtree corresponds to the length of the syntactic n-gram. Let us consider an example sentence John smoked with a little more dignity and surveyed them in silence.
In this way, the n-gram can represent the real preferences of an author when composing a text, overcoming the limitations of traditional n-grams based only on the surface information of the text. The elements that constitute syntactic n-grams can be of various types contained in the dependency relation tree, for example, lexical elements (words, lemmas, stems), POS tags, SR tags (tags of names of syntactic relations) [12,11]. There can be also mixed syntactic n-grams that contain elements of diﬀerent types.
When adding the strings of related glosses, the results increased above 40%. The different chars feature involved counting chars as types, that is, counting only the variety of characters present in the word, and its related chars itself. Finally, in addition to this, we experimented with removing stop-words from related glosses, and counting the different characters present in them. Another option we tried with the first variant was to remove everything that was not an alphabetic character. We can see very little difference with previous results.