摘要
[目的/意义]从内容挖掘的角度总结与提炼政策文本研究的主题与方向,把握政策文本研究趋势并推动创新。[研究设计/方法]主要以国内外研究论文为分析对象,采用系统性综述方法阐释政策文本领域的研究进展,经评析后展望其后续发展重点。[结论/发现]在多学科融合的政策量化与信息学研究推动下,政策文本研究的计算科学体系逐渐形成,在大数据、深度学习、人工智能等支撑下,政策文本计算和语义挖掘研究不断深入,进一步延伸至其文本功能理解和推理等方向,体现出理论、方法和技术多层面支撑的研究体系,其内在逻辑和社会应用的研究将得到加强。[创新/价值]梳理和归纳了文本内容层面的政策研究,指出了当前政策文本研究的主题以及未来的发展方向,进一步丰富了政策研究的理论与实践体系。
[Purpose/Significance]The purpose of this paper is to systematically summarize and refine the research themes and directions of policy text from the perspective of content mining.It will benefit to grasp trend and promote innovation of policy text research.[Design/Methodology]Taking domestic and foreign research articles as samples,a systematic review was conducted to elaborate the research advances of policy texts,and the key points of follow-up development were looked forward on the basis of the assessment.[Findings/Conclusion]Driven by the research on policy quantification and informatics based on multidisciplinary integration,the computational science system of policy text research has gradually developed.Meanwhile,with the support of big data,deep learning and artificial intelligence,research on computing and sematic mining of policy text has been continuously deepened.And the research on text function comprehension and inference also rises further and has received more attention.The research system of policy text is supported on multiple levels by theory,methodology and technology.Research on its internal logic and social application will be strengthened.[Originality/Value]This paper summaries the advance of policy research on the level of text content and reveals the current themes and development directions of policy development directions.This will further enrich the theoretical and practical system of policy research.
作者
胡吉明
HU Jiming(School of Information Management,Wuhan University,Wuhan 430072;Center for Studies of Information Resources,Wuhan University,Wuhan,430072;Big Data Research Institute of Wuhan University,Wuhan,430072)
出处
《图书情报知识》
北大核心
2023年第4期145-152,共8页
Documentation,Information & Knowledge
基金
湖北省青年拔尖人才培养计划项目“文本智能计算与政务精准服务”(20211011)的研究成果之一。
关键词
政策文本
政策信息学
内容计算
语义挖掘
功能理解
Policy text
Policy informatics
Content computation
Semantic mining
Function comprehension
