딥러닝을 활용한 남북한 의미 변이 탐침 방법론Detecting the Lexical Variation between South and North Koreans Using the Deep Learning Techniques
- Other Titles
- Detecting the Lexical Variation between South and North Koreans Using the Deep Learning Techniques
- Authors
- 정유남; 왕규현; 송상헌
- Issue Date
- 2021
- Publisher
- 한국어의미학회
- Keywords
- 남북한 어휘(South-North Korean Language); 노동신문(Rodong-shinmun); 단어임베딩(word embedding); 딥러닝(deep learning); 분포의미론(distributional semantics); 어휘 의미(lexical meaning); 워드투벡(Word2vec); 의미 변이(lexical variation); 조선일보(Chosun-ilbo)
- Citation
- 한국어 의미학, v.74, pp.113 - 139
- Indexed
- KCI
- Journal Title
- 한국어 의미학
- Volume
- 74
- Start Page
- 113
- End Page
- 139
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/138541
- ISSN
- 1226-7198
- Abstract
- Cheong Yunam, Wang Guehyun, Song Sanghoun. 2021. Detecting the Lexical Variation between South and North Koreans Using the Deep Learning Techniques. Korean Semantics, 74. Newspapers ordinarily reflect the meaning of lexical items in two Korean language societies and the changes in vocabulary in the times. This study proposes a methodology that automatically probes for semantic variations in which inter-Korean vocabulary differs from large-scale newspaper data. As a theoretical background, we look at the concepts of the distributional semantics and semantic variations. Next, using deep learning’s word embedding skills, we implement a system to probe semantic variations in an automatic way. This study is significant in the following respects. First, this study systematically concerns the difference in the meaning of inter-Korean vocabulary on a comprehensive scale. Second, this study draws a list of inter-Korean semantic variations by means of the deep learning techniques. Third, this study demonstrates that use of word embedding models facilitate automatic extraction of Korean semantic variations.
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