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吉林化工学院学报, 2023, 40(1): 18-22     https://doi.org/10.16039/j.cnki.cn22-1249.2023.01.005
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基于文本挖掘与知识图谱的文献计量方法研究
辛瑞昊1 , 董哲原1** , 苗冯博1** , 王甜甜1** ,李英瑞1** ,冯欣 2*
1. 吉林化工学院 信息与控制工程学院,吉林 吉林 132022;2. 吉林化工学院 理学院,吉林 吉林 132022
Research on Bibliometric Method Based on Text Mining and Knowledge Map
XIN Ruihao1, DONG Zheyuan1** , MIAO Fengbo1** ,WANG Tiantian1**, LI Yingrui1** ,FENG Xin2*
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摘要 

传统文献计量方法容易忽略文献中的文本词频,导致分析结果不能更好的突显相关领域的核心主题和研究热点,提出一种基于文本挖掘与知识图谱相联合的文献计量方法。通过共词分析构建主题词矩阵,利用共现分析、文本聚类、数据可视化和文献计量等方法分析文献核心主题和研究热点,为后续学者的研究提供参考。以高等教育改革文献为例,通过研究表明,文本挖掘和知识图谱相结合的文献计量方法可以得到高等教育改革领域的核心主题和研究热点,为高等教育改革的后续研究提供数据支撑。

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辛瑞昊
董哲原
苗冯博
王甜甜
李英瑞
冯欣
关键词:  文本挖掘  知识图谱  文献计量  高等教育改革     
Abstract: 

Traditional bibliometric methods tend to ignore the word frequency of the text in the literature, which leads to the analysis results that can't better highlight the core topics and research hotspots in related fields. This paper proposes a bibliometric method based on the combination of text mining and knowledge map. Through co-word analysis, the subject word matrix is constructed, and the core themes and research hotspots of the literature are analyzed by co-occurrence analysis, text clustering, data visualization and bibliometrics, so as to provide reference for subsequent scholars' research. Taking the literature of higher education reform as an example, the research shows that the bibliometric method combining text mining and knowledge map can obtain the core themes and research hotspots in the field of higher education reform and provide data support for the follow-up research of higher education reform.

Key words:  text mining    knowledge graph    bibliometrics    higher education reform
               出版日期:  2023-01-25      发布日期:  2023-01-25      整期出版日期:  2023-01-25
ZTFLH:  G258.6  
引用本文:    
辛瑞昊 , 董哲原 , 苗冯博 , 王甜甜 , 李英瑞 , 冯欣 . 基于文本挖掘与知识图谱的文献计量方法研究 [J]. 吉林化工学院学报, 2023, 40(1): 18-22.
XIN Ruihao, DONG Zheyuan , MIAO Fengbo , WANG Tiantian, LI Yingrui , FENG Xin. Research on Bibliometric Method Based on Text Mining and Knowledge Map . Journal of Jilin Institute of Chemical Technology, 2023, 40(1): 18-22.
链接本文:  
http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.01.005  或          http://xuebao.jlict.edu.cn/CN/Y2023/V40/I1/18
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[2] 冯欣, 苗冯博 , 王甜甜 , 董哲原 , 丛萍 , 辛瑞昊. 基于文本挖掘技术的教育类文献主题识别方法研究 [J]. 吉林化工学院学报, 2022, 39(7): 72-76.
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