The Journal of Information Systems (한국정보시스템학회지:정보시스템연구)

Korea Association of Information Systems (한국정보시스템학회)
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Research of Patent Technology Trends in Textile Materials: Text Mining Methodology Using DETM & STM

섬유소재 분야 특허 기술 동향 분석: DETM & STM 텍스트마이닝 방법론 활용

  • Received : 2021.08.31
  • Accepted : 2021.09.29
  • Published : 2021.09.30
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Abstract

Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.

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Acknowledgement

이 논문은 2021년도 산업통상자원부 산업혁신기반구축사업 재원으로 수행된 연구임.(P114000015)

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