원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.10 No.5
2015.05
pp.263-276
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper presents CSGM2, a text preprocessing technique for compression purposes. It converts the original text into a word net (graph representation) and can retain the detailed contextual information such as word proximity. Specific directed graph is proposed to model this word net where words are stored in vertices and edges represent word transitions. The word net is fully capable of holding the natural word order in the original text and hence can be used directly for encoding purposes.
목차
Abstract
1. Introduction
2. Related Work
2.1 Statistical Compression
2.2. Dictionary-based Compression
2.3. Preprocessing-based Compression
3. Natural Language Text Modeling and Compression
3.1. Graph-based Modeling for Natural Language Texts
4. The CSGM2 Transformation
4.1. Basic Concepts of Graph Theory
4.2. Word Net Building
4.3 Transforming Natural Language Text through a Word Net
5. Example
6. Conclusion
References
1. Introduction
2. Related Work
2.1 Statistical Compression
2.2. Dictionary-based Compression
2.3. Preprocessing-based Compression
3. Natural Language Text Modeling and Compression
3.1. Graph-based Modeling for Natural Language Texts
4. The CSGM2 Transformation
4.1. Basic Concepts of Graph Theory
4.2. Word Net Building
4.3 Transforming Natural Language Text through a Word Net
5. Example
6. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보