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
질문

논문 기본 정보

자료유형
학술저널
저자정보
朴敏浚 (德成女子大學校)
저널정보
중국어문학연구회 중국어문학논집 中國語文學論集 第128號
발행연도
2021.6
수록면
27 - 58 (32page)
DOI
10.25021/JCLL.2021.6.128.27

이용수

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

초록· 키워드

오류제보하기
The act of comparing is a comprehensive human cognitive process based on judgments about similarities and differences in value and degree. Inheriting its complex nature, Chinese comparative structure shows various aspects worth researching in the study of Artificial Intelligence and Linguistics. In response to this, this paper uncovers the structural, distributional features of the main Chinese equative constructions (等比句) and its semantic roles, namely Comparative Elements (CEs), based on which implemented automatic CEs extraction.
First, based on comparative prepositional phrase, the equative constructions are classified into four main categories: A. [和······相同]; B. [和/像······一样]; C. [和/像······一般]; D. [有/像······这麽(那麽)]. Next, structural and semantic differences, collocational features, and usage patterns for each type were revealed. For example, type A functions as a central predicate, while type D is mainly used as an adverbial phrase. ‘一般’ in type C generally has stronger metaphorical implication than ‘一样’ in type D, and tends to co-occur with preposition ‘像’. Finally, we established a rule-based CEs extraction model employing structural and lexical features, and measured its accuracy. As a result, we found a blind spot in which the model could not correctly recognize the comparative elements of SUB and DIM that are likely to appear remote from comparative prepositional phrases. This suggests that probabilistic approach is required to identify CEs that deviates from the marked construction.
With these findings, this paper established the basis for automatic Comparative Elements extraction by suggesting the main types and structural features of Chinese equative constructions through quantitative analysis of the actual corpus. Besides, the extraction model presented in this paper can be used to retrieve and summarize comparative information in large-scale texts such as newspapers, emails, product reviews, and social network data.

목차

1. 머리말
2. 연구대상 및 분석틀
3. 문법구조 및 특징 분석
4. 비교 의미역 식별 모델 구축 및 실험
5. 실험 결과 분석 및 결론
參考文獻
ABSTRACT

참고문헌 (34)

참고문헌 신청

함께 읽어보면 좋을 논문

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

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2021-820-001866317