By Raúl Monroy (auth.), Grigori Sidorov, Arturo Hernández Aguirre, Carlos Alberto Reyes García (eds.)
Artificial intelligence (AI) is a department of computing device technology that types 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 means of the appliance of heuristic tools simply because within the majority of instances there is not any distinctive way to this type of challenge. The Mexican overseas convention on synthetic Intelligence (MICAI), a each year foreign convention sequence geared up via the Mexican Society for synthetic Int- ligence (SMIA), is a tremendous foreign AI discussion board and the most occasion within the educational lifetime of the country’s becoming AI neighborhood. In 2010, SMIA celebrated 10 years of job on the topic of the association of MICAI as is represented in its slogan: “Ten years at the highway with AI”. MICAI meetings regularly put up high quality papers in all parts of arti- cial intelligence and its functions. The court cases of the former MICAI occasions have been additionally released through Springer in its Lecture Notes in synthetic Intelligence (LNAI) sequence, vols. 1793, 2313, 2972, 3789, 4293, 4827, 5317, and 5845. considering the fact that its foun- tion in 2000, the convention has been turning out to be in recognition and enhancing in quality.
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Additional resources for Advances in Artificial Intelligence: 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Pachuca, Mexico, November 8-13, 2010, Proceedings, Part I
One of the main difficulties of this task resides on the fact that not all similar text sections are examples of plagiarism, since thematic coincidences also tend to produce portions of common text. In order to face this problem in this paper we propose to represent the common (possibly reused) text by means of a set of features that denote its relevance and fragmentation. This new representation, used in conjunction with supervised learning algorithms, provides more elements for the automatic detection of document plagiarism; in particular, our experimental results show that it clearly outperformed the accuracy results achieved by traditional n-gram based approaches.
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 . 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   . In theses contributions SA is presented as a classification problem. A text can be categorized as objective or subjective.
Relevance and fragmentation features are complementary; their combined usage allowed obtaining a better result than their individual applications. • Results of the proposed approach, based on the combination of relevance and fragmentation features, improved by more than 7% the accuracy of the reference methods, and by more than 2% their averaged F1 measure. 30 F. Sánchez-Vega et al. Table 3. 7045 4 Conclusions and Future Work This paper describes the first ideas of a new approach for external plagiarism detection.