References
- Bae, Kyu-Yong, Park, Ju-Hyun, Kim, JeongSeon & Lee, Yung-Seop (2013). Analysis of the abstracts of research articles in food related to climate change using a text-mining algorithm. Journal of the Korean Data And Information Science Sociaty, 24(6), 1429-1437. https://doi.org/10.7465/jkdi.2013.24.6.1429
- Cho, Su-Gon & Kim, Seoung-Bum (2012). Finding Meaningful Pattern of Key Words in IIE Transactions Using Text Mining. Journal of the Korean Institute of Industrial Engineers, 38(1), 67-73. https://doi.org/10.7232/JKIIE.2012.38.1.067
- Choi, Yilang (2015). A Study on the Research Trends of Archival Studies in Korea : Focused on Research Papers between 2004 and 2013. The Korean Journal of Archival Studies, 43, 147-177. https://doi.org/10.20923/kjas.2015.43.147
- Jung, Yong-Bok & Park, Eui-Seob (2015). Keyword Analysis of Two SCI Journals on Rock Engineering by using Text Mining. Tunnel and Underground Space, 25(4), 303-319. https://doi.org/10.7474/TUS.2015.25.4.303
- Kim, Gyuha & Park, Cheolyong (2015). Analysis of English abstracts in Journal of the Korean Data & Information Science Society using topic models and social network analysis. Journal of the Korean Data And Information Science Sociaty, 26(1), 151-159. https://doi.org/10.7465/jkdi.2015.26.1.151
- Kim, Gyuhwan, Jang, BoSeong & Yi, Hyunjung (2009). A Study on Intellectual Structure of Records Management and Archives in Korea: Based on Syntactic and Semantic Structure of Article Titles. Journal of the Korean Society for Library and Information Science, 43(3), 417-439. https://doi.org/10.4275/KSLIS.2009.43.3.417
- Kim, Ji Young, Kim, Eun Hye & Lee, Ji Young (2015). A Study on the Research Trends and Knowledge Structure of Dance Management Using Text-Mining and Semantic Network Analysis. Korean Journal of Sport Management, 24(3), 85-103. https://doi.org/10.31308/KSSM.24.3.6
- Kim, Pan Jun & Suh, hye-Ran (2012). A Study on the Analysis of Intellectual Structure of Electronic Records Research in Korea Using Profiling. Journal of Korean Society of Archives and Records Management, 12(2), 29-50. https://doi.org/10.14404/JKSARM.2012.12.2.029
- Lee, Jae-Yun, Moon, Ju-Young & Kim, Hee-Jung (2007). Examining the Intellectual Structure of Records Management & Archival Science in Korea with Text Mining. Journal of the Korean Society for Library and Information Science, 41(1), 345-372. https://doi.org/10.4275/KSLIS.2007.41.1.345
- Nam, TeaWoo & Lee, Jin-Young (2009). A Study on the Research Trends of Records and Archives Management in Korea. Journal of Korean Library and Information Science Society, 40(2), 451-472. https://doi.org/10.16981/kliss.40.2.200906.451
- Park, JunHyeong & Oh, Hyo-Jung (2017). Comparison of Topic Modeling Methods for Analyzing Research Trends of Archives Management in Korea: focused on LDA and HDP. Journal of Korean Library and Information Science Society, 48(4), 235-258. https://doi.org/10.16981/kliss.48.4.201712.235
- Park, JunHyeong, Ryu, Pum-Mo & Oh Hyo-Jung (2018). Timeline-Based Topic Trend Analysis of Archives Management in Korea. Korean Society of Archives and Records Management, 18(1), 29-47. https://doi.org/10.14404/JKSARM.2018.18.1.029
- Ree, Sangbok (2019). Analysis of Research Trends in Journal of Korean Society for Quality Management by Text Mining Processing. Journal of Korean Society for Quality Management, 47(3), 597-613. https://doi.org/10.7469/JKSQM.2019.47.3.597
- Sohn, Hye In & Nam, Young Joon (2016). A Study on the Research Trends of Archives Management in Korea: Focused on the Journal of Records Management & Archives Society of Korea and The Korean Journal of Archival Studies. Journal of the Korean Society for Information Management, 33(1), 85-110. https://doi.org/10.3743/KOSIM.2016.33.1.085
- Yoon, Hee-Young & Kwak, Il-Youp (2020). The Association Modeling on Keywords and Documents of Korea International Trade Research using Paper Abstract data. Korea International Commerce Review, 35(2), 45-64. https://doi.org/10.18104/kaic.2020.35.2.45
- Ethayarajh, K., Duvenaud, D. & Hirst, G. (2019). Towards Understanding Linear Word Analogies. The Association for Computational Linguistics, 57, 3253-3262. https://doi.org/10.18653/v1/P19-1315
- Kessler, J. (2020). Visualizing thousands of phrases with Scattertext, PyTextRank and Phrasemachine. Analytics Vidhya. Available: https://medium.com/analytics-vidhya/visualizing-phrase-prominence-and-category-association-with-scattertext-and-pytextrank-f7a5f036d4d2
- Maaten, L. & Hinton, G. (2008). Visualizing Data using t-SNE. Journal of Machine Learning Research, 9, 2579-2605.
- Opacich, J. (2021). Interpreting Scattertext: A seductive tool for plotting text. Towards Data Science. Available: https://towardsdatascience.com/interpreting-scattertext-a-seductive-tool-for-plotting-text-2e94e5824858
- Parra, C., Cebollada, S., Paya, L., Holloway, M. & Reinoso, O. (2020). A Novel Method to Estimate the Position of a Mobile Robot in Underfloor Environments Using RGB-D Point Clouds. IEEE Access, 8, 9084 9101. - https://doi.org/10.1109/ACCESS.2020.2964317