서지주요정보
방향성을 이용한 상태 기반의 한국어 기반 명사구 인식 = Korean state-based baseNP identification using forward and backward processing characteristics
서명 / 저자 방향성을 이용한 상태 기반의 한국어 기반 명사구 인식 = Korean state-based baseNP identification using forward and backward processing characteristics / 이신목.
저자명 이신목 ; Lee, Sheen-Mok
발행사항 [대전 : 한국과학기술원, 2001].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8012453

소장위치/청구기호

학술문화관(문화관) 보존서고

MCS 01051

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도서상태

이용가능

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반납예정일

등록번호

9007647

소장위치/청구기호

서울 학위논문 서가

MCS 01051 c. 2

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도서상태

이용가능

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반납예정일

초록정보

BaseNP means a non-recursive noun phrase that does not contain inner noun phrases. BaseNP can be easily identified by only simple word patterns and part of speech patterns. So it is used in many areas including preprocessing phase for parsing, information extraction. BaseNP identification in Korean is studied using similar approaches as those used in English. Because of the head-final property of Korean(Cho, 1986), more global information is considered useful in Korean baseNP identification. In this thesis, we apply the state-based model that easily considers global information to Korean baseNP identification. This thesis focuses on the directionality of the state transitions in the state-based baseNP identification model. Because of the characteristics of agglutinative language, we see that, in the Korean baseNP identification, the beginning position of noun phrase is difficult to identify and the ending position is easy to identify. This fact implies that the properties and performance of the model can be changed if the state transition is processed right-to-left manner. According to this intuition, we consider not only forward-processing state-based model but also backward-processing state-based model that is newly proposed. Moreover, these two models are combined using several methods. The first one is choosing one of the two sub-results that are different from each other. The second one is applying two processing models sequentially. The performance of both forward-processing model and backward-processing model is better than that of previous models for Korean baseNP identification. Further improvement is achieved by combining two models. The precision is 92.55% and the recall is 90.90%.

서지기타정보

서지기타정보
청구기호 {MCS 01051
형태사항 iv, 39 p : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Sheen-Mok Lee
지도교수의 한글표기 : 김길창
지도교수의 영문표기 : Gil-Chang Kim
학위논문 학위논문(석사) - 한국과학기술원 : 전산학전공,
서지주기 참고문헌 : p. 36-39
주제 기반 명사구
명사구 인식
방향성
상태 기반
한국어
baseNP
identification
backward
state-based
Korean
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