Argument Mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language. Understanding argumentative structure makes it possible to determine not only what positions people are adopting, but also why they hold the opinions they do, providing valuable insights in domains as diverse as financial market prediction and public relations. This paper explores the techniques that establish the foundations for argument mining, provides a review of recent advances in argument mining techniques, and discusses the challenges faced in automatically extracting a deeper understanding of reasoning expressed in language in general.

中文翻译：

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论证挖掘：一项调查

参数挖掘是自动识别和提取以自然语言呈现的参数表示的推理和推理的结构。理解论证结构不仅可以确定人们采取什么立场，还可以确定他们为什么持有自己的观点，从而在金融市场预测和公共关系等不同领域提供有价值的见解。本文探讨了为参数挖掘奠定基础的技术，回顾了参数挖掘技术的最新进展，并讨论了自动提取对一般语言表达的推理的更深入理解所面临的挑战。