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http://dx.doi.org/10.9708/jksci.2020.25.03.109

AI Technology Analysis using Partial Least Square Regression  

Choi, JunHyeog (Dept. of Health Administration, Kimpo College)
Jun, Sunghae (Dept. of Big Data and Statistics, Cheongju University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.3, 2020 , pp. 109-115 More about this Journal
Abstract
In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.
Keywords
Artificial Intelligence; Partial Least Squares; Regression Analysis; Patent Data; Technology Analysis;
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Times Cited By KSCI : 8  (Citation Analysis)
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