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http://dx.doi.org/10.17662/ksdim.2019.15.2.019

Research Trends Analysis of Machine Learning and Deep Learning: Focused on the Topic Modeling  

Kim, Chang-Sik (세종대.배화여자대학교 글로벌관광과)
Kim, Namgyu (국민대 경영정보학부/비즈니스IT전문대학원)
Kwahk, Kee-Young (국민대 경영대학/비즈니스IT전문대학원)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.15, no.2, 2019 , pp. 19-28 More about this Journal
Abstract
The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.
Keywords
Machine Learning; Deep Learning; Artificial Neural Network; Text Mining;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
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