基于文本数据挖掘的学术期刊选题策划研究  

Study on Topic Design of Academic Periodicals:Based on Text Data Mining

作　　者：王秀芝[1] 宋迎法[1] 

机构地区：[1]中国矿业大学高等教育研究所

出　　处：《煤炭高等教育》2016年第5期122-126,共5页Meitan Higher Education

基　　金：2015年度江苏省期刊协会立项课题"基于大数据挖掘的期刊选题策划研究"(2015JSQKB010)

摘　　要：学术期刊因其专业性、学术性、创新性和文本保存形式,较适于应用文本数据挖掘开展选题策划。基于文本挖掘的学术期刊选题策划应在期刊编辑学原则的指导下,做到选题策划流程再造。本研究通过案例法阐述了文本数据挖掘应用于"一流大学与一流学科建设""高等教育国际化"两个选题的策划过程,结合编辑实践经验,提出了一条基于文本数据挖掘技术的学术期刊选题策划创新路径。Because of the characteristics of academic periodicals such as specialty, technicality, in- novation and text-saved forms, text data mining is appropriate for its topic design. Topic design of academic periodicals based on text data mining should reestablish the procedureunder the guidance of periodicals edition principle. This paper gives examples of topics design in the topics ＂first-class university and first-class disciplines＂ and ＂internationalization of higher education＂ to illustrate the text data mining process. Combining with edit experiences, the authors propose an innovative topic design path of academic periodicals based on text data mining.

关 键 词：学术期刊 文本挖掘 选题策划 

分 类 号：G232[文化科学]