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  • 标题:A Heuristic Text Analytic Approach for Classifying Research Articles
  • 本地全文:下载
  • 作者:Steven Walczak 1 , Deborah L. Kellogg
  • 期刊名称:Intelligent Information Management
  • 印刷版ISSN:2150-8194
  • 电子版ISSN:2150-8208
  • 出版年度:2015
  • 卷号:07
  • 期号:01
  • 页码:7-21
  • DOI:10.4236/iim.2015.71002
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:Classification of research articles is fundamental to analyze and understand research literature. Underlying concepts from both text analytics and concept mining form a foundation for the development of a quantitative heuristic methodology, the Scale of Theoretical and Applied Research (STAR), for classifying research. STAR demonstrates how concept mining may be used to classify research with respect to its theoretical and applied emphases. This research reports on evaluating the STAR heuristic classifier using the Business Analytics domain, by classifying 774 Business Analytics articles from 23 journals. The results indicate that STAR effectively evaluates overall article content of journals to be consistent with the expert opinion of journal editors with regard to the research type disposition of the respective journals.
  • 关键词:Bibliometric; Business Analytics; Concept Mining; Heuristic; Research Continuum; Text Analytics; Text Mining
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