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.

1. 서 론
2. 선행연구
    2.1 특허데이터 기반 기술 추세 예측
    2.2 특허 및 논문 데이터 기반 기술 추세 예측
    2.3 전문가 견해 및 텍스트마이닝 기반 기술 추세연구
    2.4 토필모델링 기반 기술 추세 연구
3. 연구방법론
    3.1 연구방법론 설계
    3.2 특허 분석 데이터 구성
    3.3 특허 분석 데이터 전처리
    3.4 LDA 토픽 모형 분석
    3.5 GPT 기반 LDA 주제의 의미추론
    3.6 전문가 견해 기반 주제의 검토 및 조정
4. 스마트팩토리 연관 특허 분석 결과
    4.1 스마트팩토리 토픽별 평균 발생빈도 분석
    4.2 스마트팩토리 토픽별 총피인용수 분석
    4.3 스마트팩토리 인용 수 분석
    4.4 스마트팩토리 패밀리특허 건수 분석
    4.5 스마트팩토리 청구항 수 분석
    4.6 스마트팩토리 독립항 수 분석
    4.7 연구 결과
5. 결 론
Acknowledgement
References

• 김상국(한국과학기술정보연구원) | Sang-Gook Kim (Korea Institute of Science and Technology Information)
• 윤민영(한국과학기술정보연구원) | Minyoung Yun (Korea Institute of Science and Technology Information)
• 권태훈(한국과학기술정보연구원) | Taehoon Kwon (Korea Institute of Science and Technology Information)
• 임정선(한국과학기술정보연구원) | Jung Sun Lim (Korea Institute of Science and Technology Information) Corresponding author