自然语言处理技术教育应用研究热点——基于NAACL会议论文的主题分析  

Research Hotspots of Educational Application of Natural Language Processing Technology——Topic Analysis Based on NAACL Conference Papers

作　　者：王萌 谢瑜阳 惠恭健 WANG Meng;XIE Yu-yang;HUI Gong-jian(School of Humanities,Jiangnan University,Wuxi 214122,China)

机构地区：[1]江南大学人文学院,江苏无锡214122

出　　处：《软件导刊》2022年第12期279-284,共6页Software Guide

基　　金：教育部人文社会科学研究项目(21YJA740037)。

摘　　要：为揭示自然语言处理技术教育应用的主题结构与演化态势,对计算机领域国际顶级会议NAACL开设的BEA专题工作坊2003-2021年论文数据,采用LDA主题模型进行语义分析,自动识别智能教学系统、阅读支持、语法错误检测、母语识别、文本自动评分等5个主题。基于识别结果对主题强度、主题新颖度、主题的演化过程进行分析,深入挖掘自然语言处理技术教育应用的研究热点。研究发现,丰富应用场景促进自然语言处理技术发展、数据驱动模型和算法研究、深度学习模型和文本表示方法等方面是研究者重点关注的内容,以期为行业人员把握最新的研究动态提供参考。In order to reveal the theme structure and evolution trend of the educational application of natural language processing technology.Based on the paper data of BEA workshop held by NAACL, an international top conference in the computer field, from 2003 to 2021, the LDA topic model is used for semantic analysis, and five topics are automatically identified, including intelligent teaching system, reading support, grammar error detection, mother tongue recognition, and text automatic scoring. Based on the recognition results, the topic intensity, the topic novelty and the topic evolution process are analyzed, and the research hotspots of the educational application of natural language processing technology are deeply explored. It is found that enriching application scenarios to promote the development of natural language processing technology, data-driven model and algorithm research, deep learning model and text representation methods are the key contents of researchers, with a view to providing reference for industry personnel to grasp the latest research trends.

关 键 词：自然语言处理 教育应用 LDA主题模型 研究热点 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术] G632.3[自动化与计算机技术—计算机科学与技术]