정보과학회논문지 : 컴퓨팅의 실제 및 레터, v.16, no.10, pp.1000-1004
ISSN
1229-7712
Publisher
한국정보과학회 (KIISE)
Language
Korean
Type
Journal Article
Abstract
형태소 품사 태거는 언어처리 시스템의 전처리기로 많이 활용되고 있다. 형태소 품사 태거의 성능 향상은 언어처리 시스템의 전체 성능 향상에 크게 기여할 수 있다. 자동번역과 같이 복잡도가 높은 언어처리 시스템은 최근 특정 도메인에서 좋은 성능을 나타내는 시스템을 개발하고 자 한다. 본 논문에서는 기존 일반도메인에서 학습된 LHMM 이나 HMM 기반의 영어 형태소 품사 태거를 특정 도메인에 적응하여 높은 성능을 나타내는 방법을 제안한다. 제안하는 방법은 특정도메인에 대한 원시코퍼스를 이용하여 HMM이나 LHMM의 기학습된 전이확률과 출력확률을 도메인에 적합하게 반자동으로 변경하는 도메인 적응 방법이다. 특허도메인에 적응하는 실험을 통하여 단어단위 태깅 정확률 98.87%와 문장단위 태깅 정확률 78.5%의 성능을 보였으며, 도메인 적응하지 않은 형태소 태거보다 단어단위 태깅 정확률 2.24% 향상(ERR: 66.4%)과 문장단위 태깅 정확률 41.0% 향상(ERR: 65.6%)을 보였다.
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