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| A Review on Methods for Domain Knowledge Evolution Analysis |
Li Xuesi1,2,Zhang Zhixiong1,2( ),Wang Yufei1,2,Liu Yi1 |
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China |
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Abstract [Objective] Domain knowledge evolution analysis has been a long-standing research topic in the field of Library and Information Science. This paper provides a comprehensive review of the research methods related to the domain knowledge evolution analysis, both nationally and internationally, aiming to offer valuable references for future studies in this area. [Coverage] We conducted searches in CNKI and Web of Science using keywords related to domain knowledge evolution. The search results were manually evaluated and analyzed, and a total of 84 key literatures closely related to the methods of domain knowledge evolution analysis were selected for review. [Methods] By reviewing the research literature, we clarified the relevant concepts of domain knowledge evolution. Based on this, we classified the existing domain knowledge evolution analysis methods into three categories: citation-based, structure-based and content-based. For each category, we first elucidated the theoretical basis, then explained their basic analytical frameworks and highlighted the relevant advances. Finally, we summarized the existing methods of domain knowledge evolution analysis and provided perspectives. [Results] The three categories of existing methods for domain knowledge evolution analysis rely on their respective scientific theories. With the advancement of technology and the improvement of data resources, these methods are continuously deepening and improving the analytical framework for the study of evolution. Although significant research achievements have been made, there has been no breakthrough in the research perspective of knowledge evolution analysis, and the limitations within the current research paradigm remain unresolved. [Limitations] The review analysis was based on selected literature, which may not have comprehensively covered all relevant research. [Conclusions] Based on the summary and analysis of the current research, we believe that the following two directions are worth focusing on in the future research on domain knowledge evolution analysis: first, exploring new entry points for domain knowledge evolution analysis, and second, attempting to integrate existing research methods to improve the limitations of current analytical approaches.
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Received: 21 November 2023
Published: 06 February 2024
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| Fund:Major Program of the National Social Science Fund of China(21&ZD329);NSTL Demonstration Platform for Semantic Content Retrieval and Analysis(2023XM21) |
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Corresponding Authors:
Zhang Zhixiong，ORCID：0000-0003-1596-7487，E-mail：zhangzhx@mail.las.ac.cn。
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