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.
崔雷,刘伟,闫雷,张晗,侯跃芳,黄莹娜,张浩. 文献数据库中书目信息共现挖掘系统的开发*[J]. 现代图书情报技术, 2008, 24(8): 70-75.
Cui Lei, Liu Wei,Yan Lei,Zhang Han,Hou Yuefang,Huang Yingna,Zhang Hao. Development of a Text Mining System Based on the Co-occurrence of Bibliographic Items in Literature Databases. New Technology of Library and Information Service, 2008, 24(8): 70-75.
