基于LDA模型和CiteSpace文献计量分析的绿色港口研究

Chen Shi, Ding Qian, Liang Ke
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引用次数: 0

摘要

随着计算机和互联网技术的飞速发展,数字信息呈现爆发式增长。传统的文本聚类模型存在数据维数高、数据稀疏、缺乏语义理解等问题。本文运用CiteSpace文献计量分析和LDA模型层次聚类方法,对绿色港口知识领域的演变过程和研究前沿进行了可视化分析,对中国绿色港口实践的深入推进具有一定的现实意义。
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Research on green port based on LDA model and CiteSpace bibliometric analysis
With the rapid development of computer and Internet technology, digital information has shown an explosive growth. Traditional text clustering models suffer from high data dimensionality, sparse data and lack of semantic understanding. This paper uses CiteSpace bibliometric analysis and LDA model hierarchical clustering method to visualise and analyse the evolution process and research frontiers of the green port knowledge domain, which has certain practical significance for the in-depth promotion of green port practices in China.
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