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http://dx.doi.org/10.6109/jkiice.2019.23.7.764

Topic Modeling on Research Trends of Industry 4.0 Using Text Mining  

Cho, Kyoung Won (Department of Healthcare Administration, Kosin University)
Woo, Young Woon (Division of Creative Software Eng., Dong-eui University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.23, no.7, 2019 , pp. 764-770 More about this Journal
Abstract
In this research, text mining techniques were used to analyze the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers and use topic modeling techniques based on LDA algorithm implemented in R language for data analysis. As a result of perplexity analysis on the collected papers, nine topics were determined optimally and nine representative topics of the collected papers were extracted using the Gibbs sampling method. As a result, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been conducted on the changes due to the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.
Keywords
Industries 4.0; Text mining; Topic modeling; Big data; KCI(Korea Citation Index);
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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