信息资源管理领域生成式人工智能:研究现状、研究主题及研究展望
Artificial Intelligence Generative Content in Information Resource Management:Research Status,Research Topics and Research Prospect
张海 1段荟 2王东波3
作者信息
- 1. 嘉兴南湖学院商贸管理学院 嘉兴 314001
- 2. 嘉兴大学商学院 嘉兴 314001
- 3. 南京农业大学信息管理学院 南京 210095
- 折叠
摘要
[研究目的]生成式人工智能与信息资源管理学科的深度融合是未来的发展趋势,因此,厘清信息资源管理领域生成式人工智能研究现状、研究主题,有助于推动生成式人工智能情境下信息资源管理学科的高质量发展.[研究方法]运用扎根理论和内容分析法对筛选出的154篇高质量文献进行概念抽取和资料整合,明确和凝练信息资源管理领域生成式人工智能研究现状和研究主题.[研究结论]研究结果显示,信息资源管理学科围绕生成式人工智能已经初步形成信息资源管理基础理论、信息技术与方法、数字人文、图书馆服务、信息管理与数据科学以及用户及其需求与行为六个研究主题.在结合研究现状、研究特征及研究主题的基础上,从理论研究和用户研究两个维度提出推动生成式人工智能与信息资源管理学科深度融合的对策与建议.
Abstract
[Research purpose]The deep integration of artificial intelligence generative content(A1GC)and information resource manage-ment is the future trend of disciplinary development.Clarifying the current research status and research topics of AIGC in information re-source management helps to promote the condensed disciplinary system of information resource management in the context of AIGC and a-chieve high-quality development.[Research method]Based on grounded theory and content analysis methods,154 high-quality papers were selected and integrated to clarify and condense the research status and themes of generative artificial intelligence in information re-source management.[Research conclusion]The research results show that information resource management has initially formed six re-search topics around AIGC,including basic theories of information resource management,information technology and methods,digital hu-manities,library services,information management and data science,and users and their needs and behaviors.Based on the current re-search status,characteristics,and themes,this article proposes strategies and suggestions from both theoretical and user research dimen-sions to promote the deep integration of AIGC and information resource management.
关键词
生成式人工智能(AIGC)/大语言模型/ChatGPT/信息资源管理/研究主题/扎根理论/内容分析法Key words
AIGC/large language model/ChatGPT/information resource management/research topic/grounded theory/content analysis methods引用本文复制引用
基金项目
国家社会科学基金重大项目(21&ZD331)
出版年
2024
国家科技期刊平台
NSTL
万方数据