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Introduction

机译:介绍

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摘要

Argument mining (also, "argumentation mining") is a relatively new research field within the rapidly evolving area of Computational Argumentation. The tasks pursued within this field are highly challenging with many important practical applications. These include automatically identifying argumentative structures within discourse, e.g., premises, conclusion, and argumentation scheme of each argument, as well as relationships between pairs of arguments and their components. To date, researchers have investigated a plethora of methods to address these tasks in various areas, including legal documents, user generated Web discourse, on-line debates, product reviews, academic literature, newspaper articles, dialogical domains, and Wikipedia articles. Relevant manually annotated corpora are released at an increasing pace, further enhancing the research in the field. In addition, argument mining is inherently tied to sentiment analysis, since an argument frequently carries a clear sentiment towards its topic. Correspondingly, this year's workshop will be coordinated with the corresponding WASSA workshop, aiming to have a joint poster session.
机译:论证挖掘(也是“论证挖掘”)是在计算论证的快速发展领域内的一个相对较新的研究领域。在该领域中追求的任务具有强大的挑战,许多重要的实际应用。这些包括自动识别话语中的论证结构,例如每个参数的场所,结论和论证方案,以及参数对与其组件的关系之间的关系。迄今为止,研究人员已经调查了一种解决各种领域的所有方法,包括法律文件,包括法律文件,用户生成的网络话语,在线辩论,产品评论,学术文学,报纸文章,对话域和维基百科文章。相关手动注释的Corpora以越来越快的速度发布,进一步提高了该领域的研究。此外,Argument Mining本质上与情感分析相关联,因为争论经常对其主题进行明显的情绪。相应地,今年的研讨会将与相应的WASSA研讨会协调,旨在进行联合海报会议。

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