메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국알타이학회 알타이학보 알타이학보 제26호
발행연도
2016.1
수록면
1 - 11 (11page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Under the Joseon Dynasty, Manchu language specialists were educated within the Joseon Court for the ceremonial necessity of making contact with the Manchu-Qing Dynasty. However, this tradition ended in the early 20th century. Kim Gugyeong was the first Korean scholar to be interested in the Manchu language and materials from the modern academic viewpoint. He was born in Seoul in 1900 and educated at Otani University in Kyoto between 1921 and 1927. Then, he established relationships with Japanese “Sinologists” including Naito Konan in Kyoto. After spending a short time working at the Keijo (Seoul) Imperial University Library on Naito’s recommendation, he moved to Beijing in 1927 and became an instructor in Japanese and Korean languages at Beijing University. In 1932, he moved to northeastern China and joined the Manchukuo National Library in Mukden as a librarian. In Beijing and Mukden in the 1930s, Kim reprinted several rare classical books related to Chinese Zen Buddhism. He is now remembered in today’s Korea as the first Korean to make contact with Chinese intellectuals such as Hu Shi, Lu Xun, and his brother, Zhou Zuoren, among others. In Beijing, Kim began to study the Manchu language and searched for old Manchu books. In Mukden, he published a revised and annotated version of the Hesei toktobuha Manjusai wecere metere kooli bithe / Qing ding man zhou ji shen ji tian dian li (edited in 1747) in 1935. After the Japanese defeat in 1945, Kim returned to Seoul and was appointed as a professor of Chinese literature at Seoul National University. However, during the Korean War, after he was captured by the North Korean Army, his whereabouts became unknown.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0