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Titlebook: Advances in Artificial Intelligence; 9th Mexican Internat Grigori Sidorov,Arturo Hernández Aguirre,Carlos Al Conference proceedings 2010 Sp

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發(fā)表于 2025-3-21 18:53:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Artificial Intelligence
期刊簡(jiǎn)稱9th Mexican Internat
影響因子2023Grigori Sidorov,Arturo Hernández Aguirre,Carlos Al
視頻videohttp://file.papertrans.cn/147/146709/146709.mp4
發(fā)行地址State-of-the-art research.Fast-track conference proceedings.Unique visibility
學(xué)科分類Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Advances in Artificial Intelligence; 9th Mexican Internat Grigori Sidorov,Arturo Hernández Aguirre,Carlos Al Conference proceedings 2010 Sp
影響因子Artificial intelligence (AI) is a branch of computer science that models the human ability of reasoning, usage of human language and organization of knowledge, solving problems and practically all other human intellectual abilities. Usually it is charact- ized by the application of heuristic methods because in the majority of cases there is no exact solution to this kind of problem. The Mexican International Conference on Artificial Intelligence (MICAI), a yearly international conference series organized by the Mexican Society for Artificial Int- ligence (SMIA), is a major international AI forum and the main event in the academic life of the country’s growing AI community. In 2010, SMIA celebrated 10 years of activity related to the organization of MICAI as is represented in its slogan: “Ten years on the road with AI”. MICAI conferences traditionally publish high-quality papers in all areas of arti- cial intelligence and its applications. The proceedings of the previous MICAI events were also published by Springer in its Lecture Notes in Artificial Intelligence (LNAI) series, vols. 1793, 2313, 2972, 3789, 4293, 4827, 5317, and 5845. Since its foun- tion in 2000, the conference has
Pindex Conference proceedings 2010
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L. C. Hoffmann,J. J. Cicchese,S. D. Berrylength of a dialogue. As innovative features, the manager accommodates the “l(fā)ounge mode” for passing all initiative back to the user within a single dialogue turn, and a two-layered structure for representing the dialogue context. At the end of the paper, we suggest future extensions to the architecture.
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https://doi.org/10.1007/978-3-642-16761-4Emotion; artificial intelligence; automatic image annotation; constrained optimization; distributed syst
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https://doi.org/10.1007/978-3-030-27852-6 develop this tool is discourse segmentation. In this work, we present DiSeg, the first discourse segmenter for Spanish, which uses the framework of Rhetorical Structure Theory and is based on lexical and syntactic rules. We describe the system and we evaluate its performance against a gold standard
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