Development of a Text Mining System Based on the Co-occurrence of Bibliographic Items in Literature Databases
文献数据库中书目信息共现挖掘系统的开发

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.