2014—2020年间论辩挖掘研讨会研究述评

Review on the Argument Mining Workshop Between 2014 and 2020

[目的/意义]论证挖掘(Argument Mining)是人工智能、文本挖掘领域近几年较为火热的研究主题,是观点挖掘(Opinion Mining)最新的研究方向。论辩挖掘旨在对文本信息中的论辩成分与结构进行识别、提取与分析,相关工作有助于度量论辩性文本中蕴含的论点、论据及其间关系,实现对观点可信度的评估,是完成文本细粒度分析和深度理解的关键。[方法/过程]本文收集了2014—2020年Argument Minging Workshop上发表的121篇论文,梳理相关理论、方法和应用场景。[结果/结论]研究发现,当前论辩挖掘研究仍处于初级阶段,相关研究存在缺乏整体性、未建立统一的标注规范、研究深度不足的缺陷。未来应更注重应用研究、提升语料库构建质量、实现从论辩性信息的理解到论辩自动生成的过渡。

[Purpose/Significance]Argument mining is the most promising research topic in the areas of artificial intelligence and text mining.It may be seen as the latest research direction of opinion mining and it aims to recognize,extract and analyze the argument components and the argument structure within the textual information.The technologies and methods of argument mining could help us to measure the claims and evidences which argumentative text carries,and to evaluate of the credibility of claims.Such works are also of fundamental importance to realize the fine-grained analysis and deep understanding of the text.[Methods/Process]In this paper,121 papers published were collected on argument mining workshop from 2014 to 2020,and were sorted out in terms of the relevant theories,methods and application scenarios.[Results/Conclusions]We find that the study of argumentation mining is still in the initial stage,and the overall researches are undermined by the shortage of holism,the absence of annotation standard,and the insufficiency of study depth.Therefore,more attention should be paid to the application research and the quality of the corpus construction in the future.Besides,it is necessarg to realize the leap from the understanding of argumentative information to the automatic generation of argumentation.