The Identification of Emerging Technologies of Automotive Semiconductor
- Authors
- Nam, Daekyeong; Choi, Gyunghyun
- Issue Date
- Feb-2023
- Publisher
- KSII-KOR SOC INTERNET INFORMATION
- Keywords
- Emerging technology; Patent Analysis; LDA Analysis; Topic Modeling; Cosine Similarity
- Citation
- KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.17, no.2, pp.663 - 677
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
- Volume
- 17
- Number
- 2
- Start Page
- 663
- End Page
- 677
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/185753
- DOI
- 10.3837/tiis.2023.02.021
- ISSN
- 1976-7277
- Abstract
- As the paradigm of future vehicles changes, the interest in automotive semiconductor, which plays a key role in realizing this, is increasing. Automotive semiconductors are the technology with very high entry barriers that require a lot of effort and time because it must secure technology readiness level and also consider safety and reliability. In this technology field, it is very important to develop new businesses and create opportunities through technology trend analysis. However, systematic analysis and application of automotive semiconductor technology trends are currently lacking. In this paper, U.S. registered patent documents related to automotive semiconductor were collected and investigated based on the patent's IPC. The main technology of automotive semiconductor was analyzed through topic modeling, and the technology path such as emerging technology was investigated through cosine similarity. We identified that those emerging technologies such as driving control for vehicle and AI service appeared. We observed that as time passed, both convergence and independence of automotive semiconductor technology proceeded simultaneously.
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