Next Article in Journal
A Study on Creative Climate in Project-Organized Groups (POGs) in China and Implications for Sustainable Pedagogy
Previous Article in Journal
Hexachlorocyclohexanes, Cyclodiene, Methoxychlor, and Heptachlor in Sediment of the Alvarado Lagoon System in Veracruz, Mexico
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Sustainability 2018, 10(1), 115; https://doi.org/10.3390/su10010115

Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

1
Graduate School of Management of Technology, Korea University, Seoul 02841, Korea
2
Department of Statistics, Cheongju University, Chungbuk 28503, Korea
3
Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea
*
Author to whom correspondence should be addressed.
Received: 8 December 2017 / Revised: 3 January 2018 / Accepted: 4 January 2018 / Published: 5 January 2018
(This article belongs to the Section Economic, Business and Management Aspects of Sustainability)
Full-Text   |   PDF [536 KB, uploaded 5 January 2018]   |  

Abstract

Recent developments in artificial intelligence (AI) have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology. View Full-Text
Keywords: artificial intelligence; patent technology analysis; sustainable technology; Bayesian inference; social network analysis artificial intelligence; patent technology analysis; sustainable technology; Bayesian inference; social network analysis
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Kim, J.; Jun, S.; Jang, D.; Park, S. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models. Sustainability 2018, 10, 115.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top