상세정보
학술지
Dependency Structure Language Model for Topic Detection and Tracking
- 발행일
- 200709
- 출처
- Information Processing & Management, v.43 no.5, pp.1249-1259
- ISSN
- 0306-4573
- 출판사
- Elsevier
- 협약과제
- 06MW1800, 신성장동력산업용 대용량 대화형 분산 처리 음성인터페이스 기술개발, 이영직
- 초록
- In this paper, we propose a new language model, namely, a dependency structure language model, for topic detection and tracking (TDT) to compensate for weakness of unigram and bigram language models. The dependency structure language model is based on the Chow expansion theory and the dependency parse tree generated by a linguistic parser. So, long-distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model on topic tracking and link detection in TDT. In both cases, the dependency structure language models perform better than strong baseline approaches. © 2006.
- KSP 제안 키워드
- Dependency Parse, Dependency Structure, Language model, Long-distance, Parse tree, Proposed model, Topic tracking, topic detection and tracking