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Evolution of Topics About Medical Informatics by Improved Co-word Cluster Analysis
应用改进的共词聚类法探索医学信息学热点主题演变

Keywords: Co-word analysis,Visualization,Cluster,Adhesive force,Zipf’s law
共词分析
,可视化,聚类,粘合力,齐普夫定律

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Abstract:

Co-word cluster method is improved by following ways: high-frequency words are selected according to the formula derived from Zipf’s law; adhesive force is used to identify the core major MeSH words for tagging the content of each cluster; contrastive analysis of two periods helps to find the topics change. The bibliographic data of medical informatics are collected from PubMed in two periods (1999-2003 and 2004-2008). Major MeSH words from the articles are extracted separately to make co-word clusters as to explore the evolution of this subject structure based on comparison of two periods.

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