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Ma, J., Xu, W., Sun, Y., Turban, E., Wang, S. and Liu, O. (2012) An Ontology-Based Text Analytics Method to Cluster Proposals for Research Project Selection. Transactions on Systems, Man, and Cybernetics—Part A, 42, 784-790.http://dx.doi.org/10.1109/TSMCA.2011.2172205

has been cited by the following article:

• TITLE: A Heuristic Text Analytic Approach for Classifying Research Articles

  AUTHORS: Steven Walczak, Deborah L. Kellogg

  KEYWORDS: Bibliometric, Business Analytics, Concept Mining, Heuristic, Research Continuum, Text Analytics, Text Mining

  JOURNAL NAME: Intelligent Information Management, Vol.7 No.1, January 26, 2015

  ABSTRACT: 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.