의미연결망과 토픽모델링을 활용한 스마트 도시재생 연구동향 분석
Analysis of Smart Urban Regeneration Research Trends Using Semantic Network and Topic modeling
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초록
The purpose of this study is to analyze the research topics and research trends of smart urban regeneration research by period. For this study, information such as titles, abstracts, and years of 95 academic papers and 162 theses related to smart city regeneration registered in the Korean Journal Citation Index (KCI) was extracted and analyzed. Specifically, the semantic network and topic modeling analysis were performed using the NetMiner 4.5 program. As a result of the analysis, studies related to smart urban regeneration have increased rapidly since 2018, and the frequency of words such as local government, region, energy, analysis, and plan was high. K-means clustering analysis was reached to the end, and based on the above, 7 topics were minimized, and 7 keywords were stretched out for each topic through the LDA algorithm. As a result, Topic4, which has sustainability, community, and cooperation as keywords, was able to classify the most weighting picks into topics, and topic modeling analysis was analyzed by classifying them based on the past 2018 in relation to smart urban regeneration.The common point before and after 2018 is that it seeks to form a base-oriented community through the integration and integration of technologies and to preserve the identity of the region based on convenience. The difference is that before 2018, research related to smart urban regeneration was conducted centering on urban image and eco-friendly design, but after 2018, smart technology was applied to industry, environment, and regionally specialized resources to realize sustainable smart urban regeneration based on the region.
Abstract
The purpose of this study is to analyze the research topics and research trends of smart urban regeneration research by period. For this study, information such as titles, abstracts, and years of 95 academic papers and 162 theses related to smart city regeneration registered in the Korean Journal Citation Index (KCI) was extracted and analyzed. Specifically, the semantic network and topic modeling analysis were performed using the NetMiner 4.5 program. As a result of the analysis, studies related to smart urban regeneration have increased rapidly since 2018, and the frequency of words such as local government, region, energy, analysis, and plan was high. K-means clustering analysis was reached to the end, and based on the above, 7 topics were minimized, and 7 keywords were stretched out for each topic through the LDA algorithm. As a result, Topic4, which has sustainability, community, and cooperation as keywords, was able to classify the most weighting picks into topics, and topic modeling analysis was analyzed by classifying them based on the past 2018 in relation to smart urban regeneration.The common point before and after 2018 is that it seeks to form a base-oriented community through the integration and integration of technologies and to preserve the identity of the region based on convenience. The difference is that before 2018, research related to smart urban regeneration was conducted centering on urban image and eco-friendly design, but after 2018, smart technology was applied to industry, environment, and regionally specialized resources to realize sustainable smart urban regeneration based on the region.
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