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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- (사)국제문화기술진흥원 The International journal of advanced culture technology The International journal of advanced culture technology 제7권 제4호
- 발행연도
- 2019.1
- 수록면
- 295 - 301 (7page)
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초록· 키워드
오류제보하기
Since the third artificial intelligence boom was triggered by deep learning, it has been 10 years. It is time to analyze and discuss the research trends of deep learning for the stable development of AI. In this regard, this study systematically analyzes the trends of research on deep learning over the past 10 years. We collected research literature on deep learning and performed LDA based topic modeling analysis. We analyzed trends by topic over 10 years. We have also identified differences among the major research countries, China, the United States, South Korea, and United Kingdom. The results of this study will provide insights into research direction on deep learning in the future, and provide implications for the stable development strategy of deep learning.
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등록된 정보가 없습니다.
참고문헌 (9)
참고문헌 신청
Yann LeCun / 2015 / Deep learning / Nature 521(7553):436~444
Alexandra Amado / 2018 / Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis / European Research on Management and Business Economics 24(1):1~7
이지영 / 2019 / A Study on Research Trend Analysis and Topic Class Prediction of Digital Transformation using Text Mining / The International Journal of Advanced Smart Convergence 8(2):183~190
David M. Blei / 2012 / Probabilistic topic models / Communications of the ACM 55(4):77~84
Steyvers, M. / 2007 / Probabilistic topic models / Handbook of latent semantic analysis 427(7):424~440
Alexandra Amado / 2018 / Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis / European Research on Management and Business Economics 24(1):1~7
이지영 / 2019 / A Study on Research Trend Analysis and Topic Class Prediction of Digital Transformation using Text Mining / The International Journal of Advanced Smart Convergence 8(2):183~190
David M. Blei / 2012 / Probabilistic topic models / Communications of the ACM 55(4):77~84
Steyvers, M. / 2007 / Probabilistic topic models / Handbook of latent semantic analysis 427(7):424~440
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