文献数据库中书目信息共现挖掘系统的开发

Development of a Text Mining System Based on the Co-occurrence of Bibliographic Items in Literature Databases

针对权威的生物医学数据库和引文索引数据,介绍一个基于文献数据库中书目信息共现关系进行文本挖掘的系统。该系统具有基本的文献计量学分析功能,并对相应的结果进行可视化表达;对高频主题词、高产作者和高被引论文和高被引作者进行共现分析,据此进行聚类分析和关联分析,获得有关的研究主题聚类和主题词/副主题词关联规则、合著聚类分析、高被引论文同被引聚类分析和高被引作者同被引聚类分析的结果和可视化表达。其中对关联规则的分析可以发现主题词之间的潜在语义规则,其他的文献计量学指标和共现分析结果可以用于科学计量学的分析。

This paper presents a text mining system based on the co - occurrence of bibliographic items in literature databases. This system produces the principal bibliometric indicators of a given document set oriented to PubMed and Web of Science, and some of results are presented by visualization techniques. Further more, it provides cluster analysis and association analysis by investigating the co - occurrence data of high - frequent MeSH terms, high - productive authors, highly - cited papers and highly - cited authors. Using these approaches users can mining the potential association rules among MeSH terms, and engage scientometric investigations.