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Conference Paper
Extracting Promising Topics on Smart Manufacturing Based on Latent Dirichlet Allocation (LDA)
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- Authors
- Young Seog Yoon, Junhee Lee, Kwangroh Park
- Issue Date
- 2019-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1237-1242
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- 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.
- KSP Keywords
- Big Data, Cloud Manufacturing, Internet of thing(IoT), Latent dirichlet allocation (lda), Product information management, Smart Manufacturing, cyber physical system(CPS), industrial internet of things