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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.3 No.3
- 발행연도
- 2009.9
- 수록면
- 143 - 164 (22page)
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초록· 키워드
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This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and future trends.
목차
1. INTRODUCTION
2. STATISTICAL LANGUAGE MODELING
3. LANGUAGE MODELING APPROACHES TO INFORMATION RETRIEVAL
4. SMOOTHING STUDIES
5. SEMANTICS AND THE LANGUAGE MODELING FRAMEWORK
6. LANGUAGE MODELING AND XML RETRIEVAL
7. FUTURE TRENDS
8. CONCLUSION
REFERENCES
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