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The Identification of Emerging Technologies of Automotive Semiconductor

Authors
Nam, DaekyeongChoi, 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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CHOI, GYUNG HYUN
GRADUATE SCHOOL OF TECHNOLOGY & INNOVATION MANAGEMENT (DEPARTMENT OF TECHNOLOGY MANAGEMENT)
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