摘要翻译:
传统的舞台是基于一种形式的相似性方法,依靠戏剧本体和实例化变异。受交互式数据挖掘的启发,提出了不同的方法,我们概述了计算机科学和戏剧研究,使用计算机作为演员的搭档来逃避角色的先验规范。
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英文标题:
《Similarit\'e en intension vs en extension : \`a la crois\'ee de
l'informatique et du th\'e\^atre》
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作者:
Alain Bonardi (STMS), Francis Rousseaux (STMS, CRESTIC)
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最新提交年份:
2009
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要:
Traditional staging is based on a formal approach of similarity leaning on dramaturgical ontologies and instanciation variations. Inspired by interactive data mining, that suggests different approaches, we give an overview of computer science and theater researches using computers as partners of the actor to escape the a priori specification of roles.
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PDF链接:
https://arxiv.org/pdf/0912.4879