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Towards Mathematical AI via a Model of the Content and Process of Mathematical Question and Answer Dialogues

机译:通过数学问题的内容和过程的模型向数学AI对话和回答对话

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This paper outlines a strategy for building semantically meaningful representations and carrying out effective reasoning in technical knowledge domains such as mathematics. Our central assertion is that the semi-structured Q&A format, as used on the popular Stack Exchange network of websites, exposes domain knowledge in a form that is already reasonably close to the structured knowledge formats that computers can reason about. The knowledge in question is not only facts - but discursive, dialectical, argument for purposes of proof and pedagogy. We therefore assert that modelling the Q&A process computationally provides a route to domain understanding that is compatible with the day-to-day practices of mathematicians and students. This position is supported by a small case study that analyses one question from Mathoverflow in detail, using concepts from argumentation theory. A programme of future work, including a rigorous evaluation strategy, is then advanced.
机译:本文概述了建立语义有意义的陈述的策略,并在数学等技术知识域中进行有效推理。我们的中央断言是,在流行的网站上使用的半结构化Q&A格式公开了已经合理地接近计算机可以推理的结构化知识格式的形式的域知识。有问题的知识不仅是事实 - 而是有话语,辩证,辩证,辩称的论点,用于证明和教育学的目的。因此,我们断言,建模Q&A进程计算地提供了与数学家和学生的日常实践兼容的域理解的路由。该职位得到了一个小写的研究支持,使用论证理论的概念详细分析了Mathoverflow的一个问题。然后,将进入未来的工作计划,包括严格的评估策略,然后是先进。

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