Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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A Study on Big Data Analysis of Related Patents in Smart Factories Using Topic Models and ChatGPT

토픽 모형과 ChatGPT를 활용한 스마트팩토리 연관 특허 빅데이터 분석에 관한 연구

  • Sang-Gook Kim (Korea Institute of Science and Technology Information) ;
  • Minyoung Yun (Korea Institute of Science and Technology Information) ;
  • Taehoon Kwon (Korea Institute of Science and Technology Information) ;
  • Jung Sun Lim (Korea Institute of Science and Technology Information)
  • Received : 2023.09.26
  • Accepted : 2023.10.24
  • Published : 2023.12.31
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Abstract

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

Keywords

Acknowledgement

This research received partial funding from two programs (K-23-L05-C02-S16, K-23-L03-C04-S01) provided by the Korea Institute of Science and Technology Information (KISTI) in South Korea.

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