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Text Mining Method for Building New Business Strategies

Focusing on the Neurosurgical Robot
  • Fumio KomodaEmail author
  • Yoshihiro Muragaki
  • Ken Masamune
Chapter

Abstract

In any time, it has been essential to acquire knowledge of customer needs and global trends of technological progress for proper selection and concentration strategy planning, which is decisive for long-term growth of the company. However, with the change in innovation paradigm, the methods used for its acquisition have also changed. With the era of big data, text mining that gains knowledge necessary for this planning from unstructured natural language with weak affinity with relational databases has attracted attention recently. However, in order to obtain highly accurate and reliable knowledge that can contribute to company decision-making, the current natural language processing algorithm is not sufficient. Current text mining method, which is limited to bird’s eye viewing type aimed at capturing the entire text data roughly, is unsuitable for finding out important knowledge written only in a very small part of the text data. Therefore, this paper presents the virtual case of a company planning a new neurosurgical robot project and applies pinpoint focus type text mining technique to acquiring technological knowledge from high-impact peer-reviewed academic journals.

Keywords

Text mining Pinpoint focus type text mining Innovation paradigm Text data Business strategy Neurosurgical robot 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Fumio Komoda
    • 1
    Email author
  • Yoshihiro Muragaki
    • 2
  • Ken Masamune
    • 2
  1. 1.Honorary ProfessorSaitama UniversitySaitamaJapan
  2. 2.Institute of Advanced Bio-Medical Engineering and ScienceTokyo Women’s Medical UniversityTokyoJapan

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