关键词提取研究综述  

Review of Keyword Extraction Studies

作　　者：胡少虎 张颖怡[1] 章成志[1] Hu Shaohu;Zhang Yingyi;Zhang Chengzhi(School of Economics and Management,Nanjing University of Science&Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学经济管理学院,南京210094

出　　处：《数据分析与知识发现》2021年第3期45-59,共15页Data Analysis and Knowledge Discovery

基　　金：国家自然科学基金面上项目(项目编号:72074113)的研究成果之一。

摘　　要：【目的】对关键词提取研究的主要方法、相关特征以及评价方法进行总结梳理,为后续的关键词提取研究提供借鉴。【文献范围】以"Keyword Extraction"、"Keyword Generation"、"Keyphrase Extraction"、"Keyphrase Generation"、"关键词抽取"、"关键词生成"等检索式在Web of Science、DBLP、Engineering Index、Google Scholar、CNKI和万方等数据库进行检索,结合个人积累与文献溯源得到代表性文献89篇。【方法】梳理关键词提取的发展脉络,从研究方法、相关特征与评价方法三个主要方面对关键词提取的相关研究进行深入分析与总结。【结果】关键词提取方法随着机器学习技术的发展,逐步从特征驱动的模型转向数据驱动的模型,并面临数据标注、评价规范等问题。【局限】更为关注关键词提取研究中主流的方法。【结论】本文通过对关键词提取方法,尤其是关键词生成方法进行总结,阐明了关键词提取方法的研究重心从特征转向数据的趋势与原因,并指出现有关键词提取评价体系所存在的缺陷。[Objective] This paper reviews the methods, features and evaluation procedures of keyword extraction research, aiming to provide reference for future studies. [Coverage] We searched the Web of Science, DBLP,Engineering Index, Google Scholar, CNKI and Wanfang Data with "Keyword Extraction", "Keyword Generation"",Keyphrase Extraction", and"Keyphrase Generation", etc. A total of 89 representative literature were retrieved. [Methods] First, we analyzed the development of keyword extraction techniques. Then, we summarized related studies from the perspectives of research methods, characteristics and evaluation process.[Results] The keyword extraction methods, which gradually shifted from feature-driven models to data-driven models due to the development of machine learning, also faced problems like data labeling and evaluation criteria. [Limitations] We examined more mainstream methods for keyword extraction. [Conclusions] This paper summarizes the developing trends of keyword extraction methods, as well as the dis-advantages of existing evaluation mechanism.

关 键 词：提取 关键词抽取 关键词生成 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] G250[自动化与计算机技术—计算机科学与技术]