Ensemble modeling for sustainable technology transfer

Junseok Lee, Ji Ho Kang, Sunghae Jun, Hyunwoong Lim, Dong Sik Jang, Sangsung Park

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

These days, technological advances are being made through technological conversion. Following this trend, companies need to adapt and secure their own sustainable technological strategies. Technology transfer is one such strategy. This method is especially effective in coping with recent technological developments. In addition, universities and research institutes are able to secure new research opportunities through technology transfer. The aim of our study is to provide a technology transfer prediction model for the sustainable growth of companies. In the proposed method, we first collected patent data from a Korean patent information service provider. Next, we used latent Dirichlet allocation, which is a topic modeling method used to identify the technical field of the collected patents. Quantitative indicators on the patent data were also extracted. Finally, we used the variables that we obtained to create a technology transfer prediction model using the AdaBoost algorithm. The model was found to have sufficient classification performance. It is expected that the proposed model will enable universities and research institutes to secure new technology development opportunities more efficiently. In addition, companies using this model can maintain sustainable growth in line, coping with the changing pace of society.

Original languageEnglish
Article number2278
JournalSustainability (Switzerland)
Volume10
Issue number7
DOIs
Publication statusPublished - 2018 Jul 2

Keywords

  • Ensemble model
  • Latent Dirichlet allocation
  • Prediction model
  • Technology topic
  • Technology transfer

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

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