Performance Comparison on Automated Generation of Coding Rules: A Case Study on ISO 26000

  • Tetsuya Nakatoh Kyushu University
  • Satoru Uchida Kyushu University
  • Emi Ishita Kyushu University
  • Toru Oga Kyushu University
Keywords: Text mining, Coding rules, Automated Generation, SVM, ISO 26000

Abstract

When texts are mined for meaningful information, one important aspect is to construct a coding rule that categorizes key terms into several conceptual groups. Usually, such a rule is human-made and tends to be subjective. The present study attempts to build coding rules automatically from the ISO 26000 document by using two proposed methods. The results were compared with the manually created coding rules, and the SVM method was proven to be more effective.

Author Biographies

Tetsuya Nakatoh, Kyushu University

Assistant Professor

Academic Information Section,
Research Institute for Information Technology

Satoru Uchida, Kyushu University
Faculty of Languages and Cultures
Emi Ishita, Kyushu University
Research and Development Division, Kyushu University Library
Toru Oga, Kyushu University
Faculty of Law

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Published
2017-06-30