Browse > Article
http://dx.doi.org/10.9720/kseg.2021.3.307

Domain Analysis of Research on Prediction and Analysis of Slope Failure by Co-Word Analysis  

Kim, Sun-Kyum (Korea Institute of Civil Engineering and Building Technology)
Kim, Seung-Hyun (Korea Institute of Civil Engineering and Building Technology)
Publication Information
The Journal of Engineering Geology / v.31, no.3, 2021 , pp. 307-319 More about this Journal
Abstract
Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.
Keywords
slope failure; analysis; domain structure; co-word analysis; network analysis; cluster analysis;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Lee, J.Y., 2013, A comparison study on the weighted network centrality measures of tnet and WNET, Journal of the Korean Society for Information Management, 30(4), 241-264 (in Korean with English abstract).   DOI
2 Lee, K.B., Shin, H.S., Kim, S.H., Ha, D.M., Choi, I., 2019, A study on automatic classification of characterized ground regions on slopes by a deep learning based image segmentation, Tunnel and Underground Space, 29(6), 508-522 (in Korean with English abstract).   DOI
3 Seo, S.K., Chung, E.K., 2013, Domain analysis on the field of open access by co-word analysis, Journal of the Korean BIBLIA Society for Library and Information Science, 24(1), 207-228 (in Korean with English abstract).   DOI
4 Park, D.G., Kim, T.H., Park, J.H., 2006, Status and countermeasures of slope damage in Korea, Geotechnical Engineering, 22(6), 6-18.
5 Lee, J.Y., 2006a, A study on the network generation methods for examining the intellectual structure of knowledge domains, Journal of the Korean Society for Library and Information Science, 40(2), 333-355 (in Korean with English abstract).   DOI
6 Hansen, D., Shneiderman, B., Smith, M.A., 2011, Analyzing social media networks with NodeXL: Insights from a connected world, Morgan Kaufmann, 283p.
7 Kim, S.H., Koo, H.B., Hwang, J.H., Son, M., 2011, Case study on the cause of failure and characteristics of soil at a collapsed cut-slope at the ◯◯ Detour, Jeonranam-Do, The Journal of Engineering Geology, 21(4), 313-322 (in Korean with English abstract).   DOI
8 Lee, J.Y., 2006c, Centrality measures for bibliometric network analysis, Journal of the Korean Society for Library and Information Science, 40(3), 191-214 (in Korean with English abstract).   DOI
9 MLTM (Ministry of Land, Transport and Maritime Affairs), 2011, Roadside slope maintenance manual, 495p.
10 Lee, J.Y., 2006b, A novel clustering method for examining and analyzing the intellectual structure of a scholarly field, Journal of the Korean Society for Information Management, 23(4), 215-231 (in Korean with English abstract).   DOI
11 White, H.D., Griffith, B.C., 1981, Author cocitation: A literature measure of intellectual structure, Journal of the American Society for Information Science, 32(3), 163-171.   DOI