International Journal of Social Science & Economic Research
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Title:
SUSTAINABLE TECHNOLOGY MINING USING STATISTICAL MODELING

Authors:
Sunghae Jun

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Sunghae Jun
Professor, Department of Big Data and Statistics, Cheongju University, Chungbuk 28503 Korea

MLA 8
Jun, Sunghae. "SUSTAINABLE TECHNOLOGY MINING USING STATISTICAL MODELING." Int. j. of Social Science and Economic Research, vol. 3, no. 12, Dec. 2018, pp. 6669-6679, ijsser.org/more2018.php?id=469. Accessed Dec. 2018.
APA
Jun, S. (2018, December). SUSTAINABLE TECHNOLOGY MINING USING STATISTICAL MODELING. Int. j. of Social Science and Economic Research, 3(12), 6669-6679. Retrieved from ijsser.org/more2018.php?id=469
Chicago
Jun, Sunghae. "SUSTAINABLE TECHNOLOGY MINING USING STATISTICAL MODELING." Int. j. of Social Science and Economic Research 3, no. 12 (December 2018), 6669-6679. Accessed December, 2018. ijsser.org/more2018.php?id=469.

References
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Abstract:
Sustainable technology is a technology that can sustain the technological competitiveness of a company continuously. So, it is important to forecast and understand the sustainable technology. This paper deals with statistical modelling for sustainable technology mining. We use association rule mining, social network analysis, and linear regression for constructing statistical model. In this paper, we combine the results of three analytical methods for sustainable technology analysis. To verify the performance and validity of our research, we carry out case study on the technology domain related to artificial intelligence.