摘要： 目的 对PubMed中倒班相关文献的高频主要主题词和副主题词进行共词聚类分析，获取主题词之间的关联规则，并对该领域内主题词之间的潜在语义关系进行挖掘，分析倒班相关主题的研究热点。方法 运用BICOMS和gCluto软件对PubMed数据库中倒班相关文献进行处理，获得双聚类矩阵图，经分析后得到该领域近年来的研究主题方向与热点。结果 通过聚类簇山峰图谱、可视化双聚类词篇矩阵，结合语义分析，结果显示倒班相关研究以八大主题为主。结论 通过文献的共词聚类分析，能为该领域研究人员了解现状以及开展相关研究提供参考。

基于双聚类方法的国际倒班相关文献研究热点分析

冯会玲^1,2, 范玲^2,3

1. 河北中医学院护理学院外科护理教研室, 石家庄 050200;
2. 中国医科大学护理学院, 沈阳 110122;
3. 中国医科大学附属盛京医院护理部, 沈阳 110004

收稿日期:2020-12-01出版日期:2021-07-30发布日期:2021-06-24
通讯作者:范玲E-mail:Fanl@sj_hospital.org
作者简介:冯会玲(1986-),女,讲师,博士研究生.
基金资助:河北省科学技术厅2018年省重点研发计划指导项目（辽科发［2018］24号）


关键词: 倒班, 研究热点, 双聚类分析, 文本挖掘
Abstract: Objective In this study,we conduct co-word clustering analysis on the high-frequency main topic words and subtopic words in the shift-related literature from PubMed. Further,to obtain the association rules between the topic words,and the potential between the topic words in the field,semantic relationship mining and analysis of international research hotspots related to shifts was conducted. Methods We used BICOMS and gCluto software to process the shift-related literature in the PubMed database and obtained the bi-clustering matrix diagram,the research topic directions,and hot spots in this field (in recent years) after analysis. Results Through clustering mountain peak maps and visualizing bi-clustering word-text matrix,combined with semantic analysis,we found that the shift-related research focuses on eight themes. Conclusion The co-word cluster analysis of the literature can provide a reference for researchers in this field to understand the status quo to be able to carry out related research.
Key words: shift work, research hotspot, bi-clustering analysis, text mining
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