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학술대회 Extracting Promising Topics on Smart Manufacturing Based on Latent Dirichlet Allocation (LDA)
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저자
윤영석, 이준희, 박광로
발행일
201910
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1237-1242
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939701
협약과제
19PH2500, 지능형 신발공장을 위한 통합관리시스템 개발, 박광로
초록
Although smart manufacturing (SM) has attracted enormous attention, it is ambiguous how to realize it due to lack of practical evidence and academic knowledge on technological components. Accordingly, it is required to explore knowledge landscape to investigate promising technologies. For this purpose, this study extracts 35 topics discussed in abstracts in previous literatures by employing Latent Dirichlet Allocation. The analysis results unveil big data, product information management, cyber-physical system, cloud manufacturing platform, and industrial Internet of things are identified as promising topics. It is also noteworthy that SM needs a unified vision because topics are diverged rather than converged.
키워드
intelligent manufacturing, Latent Dirichlet Allocation, LDA, smart manufacturing, topics
KSP 제안 키워드
Big Data, Cloud Manufacturing, Intelligent Manufacturing, Internet of thing(IoT), Latent dirichlet allocation (lda), Product information management, Smart Manufacturing, cyber physical system(CPS), industrial internet of things