MEASURING CONTRIBUTION OF SPATIAL INFORMATION TO ENVIRONMENTAL RESEARCH USING TEXT MINING TECHNIQUES

被引：0
|
作者：
Lee, Jeongho [1 ]
Lee, Moung-Jin [1 ]
机构：
[1] Korea Environm Inst KEI, Sejong, South Korea
来源：
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年
关键词：
Text mining; Environmental spatial information; Frequency analysis; Reciprocal relevance analysis;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This study aimed to quantitatively analyze the trends of environmental research that utilizes environmental spatial information using a text mining technique. The analysis was conducted on a total of 869 papers published in Korea based on 20 environmental spatial information areas, and the results showed that 1) "general environment (40.85%)" and "satellite image (24.87%)" had the highest frequency levels among the environmental spatial information areas, and 2) a total of 80 relevance rules were generated on environmental spatial information, indicating that "general environment" generated the highest number of correlation rules (17) with environmental spatial information such as "satellite image" and "digital map."
引用
收藏
页码：5289 / 5291
页数：3
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