Download Advances in Artificial Intelligence: 9th Mexican by Raúl Monroy (auth.), Grigori Sidorov, Arturo Hernández PDF

By Raúl Monroy (auth.), Grigori Sidorov, Arturo Hernández Aguirre, Carlos Alberto Reyes García (eds.)

Artificial intelligence (AI) is a department of desktop technological know-how that versions the human skill of reasoning, utilization of human language and association of data, fixing difficulties and essentially all different human highbrow talents. frequently it's charact- ized by way of the appliance of heuristic tools simply because within the majority of instances there is not any designated strategy to this type of challenge. The Mexican foreign convention on synthetic Intelligence (MICAI), a every year foreign convention sequence geared up via the Mexican Society for man made Int- ligence (SMIA), is an important overseas AI discussion board and the most occasion within the educational lifetime of the country’s growing to be AI neighborhood. In 2010, SMIA celebrated 10 years of task on the topic of the association of MICAI as is represented in its slogan: “Ten years at the street with AI”. MICAI meetings regularly put up high quality papers in all components of arti- cial intelligence and its purposes. The complaints of the former MICAI occasions have been additionally released by way of Springer in its Lecture Notes in synthetic Intelligence (LNAI) sequence, vols. 1793, 2313, 2972, 3789, 4293, 4827, 5317, and 5845. because its foun- tion in 2000, the convention has been starting to be in reputation and bettering in quality.

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Extra info for Advances in Artificial Intelligence: 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Pachuca, Mexico, November 8-13, 2010, Proceedings, Part I

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The need for sentiment analysis is the outcome of sudden increase in the opinionated or sentimental text, which is in the form of blogs, reviews, and discussions [1]. The main feature of such text is its variability in structure, style, and vocabulary. Researchers have made great attempts to cope with this variability issue. Some of the contributions are quite successful like [2] [3] [4]. In theses contributions SA is presented as a classification problem. A text can be categorized as objective or subjective.

Sidorov et al. ): MICAI 2010, Part I, LNAI 6437, pp. 13–23, 2010. © Springer-Verlag Berlin Heidelberg 2010 14 I. da Cunha et al. In this paper we present DiSeg, the first discourse segmenter for Spanish. It produces state of the art results while it does not require syntactic analysis but only shallow parsing with a reduced set of linguistic rules. Therefore it can be easily included in applications that require fast text analysis on the fly. In particular it will be part of the discourse parser for Spanish that we are carrying out.

Cases of particular interest are the fm features, which indicate the values of all sequences with length equal or greater than m (a user-defined value). Their purpose is to deal with the data sparseness and to allow taking advantage of the occurrence of discriminative but very rare longer sequences. Following we define both kind of features. For the sake of simplicity we first describe fragmentation features and afterward relevance features. Fragmentation features. By means of these features we aim to find a relation between the length and quantity of common sequences and the plagiarism.

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