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Text mining method to identify artificial intelligence technologies for the semiconductor industry in Korea

Authors
Cho, InsuJu, Yonghan
Issue Date
Sep-2023
Publisher
Elsevier Ltd
Keywords
International patent classification; Network analysis; Patent; Semiconductor; Text mining
Citation
World Patent Information, v.74
Journal Title
World Patent Information
Volume
74
URI
https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/49448
DOI
10.1016/j.wpi.2023.102212
ISSN
0172-2190
Abstract
Semiconductors are among the most important core technologies contributing to the Fourth Industrial Revolution. The United States, Taiwan, and China have been investing heavily in semiconductor research and development. To achieve international competitiveness in the semiconductor industry, Korea needs to establish a research and development (R&D) roadmap for small- and medium-sized enterprises (SMEs). Our study identified trends in the semiconductor industry by analyzing the characteristics of core technologies based on patents that disclose technologies instead of holding exclusive ownership. Specifically, we analyzed registered patents concerned with artificial intelligence and machine learning pertaining to the semiconductor industry, which are attracting considerable attention. Using the Korea Intellectual Property Rights Information Service database, we identified 3569 patent specifications related to AI technology and the semiconductor industry. The text mining and network analysis results indicated that the application of deep neural networks is the most important and affects various aspects of R&D. Particularly, AI technology is actively studied for monitoring manufacturing and etch processes. Additionally, technology convergence among virtual reality, visualization, smart factories, and etching technology was identified. The analysis results identify promising technologies related to semiconductors and provide insights that would enable SMEs in the Korean semiconductor industry to establish a technology roadmap. © 2023
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