원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.2 No.2
2009.04
pp.105-116
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
With the proliferation of the Internet and the huge amount of data it transfers, automatic text summarization is becoming more important. In this paper we first analyze some state of the art methods to text summarization., We also try to analyze one of the previous text summarization methods, "Machine learning Approach", and eliminate its shortcomings .Finally we present an approach to the design of an automatic text summarizer that generates a summary using fuzzy logic to obtain better results compared to previous methods.
목차
Abstract
1. Introduction
2. Summarization Approaches
2.1. Statistical Approach
2.2. Linguistic Approach
3. A Review of Text Summarization Based on Machine Learning
4. The Used Attribute in Text Summarization
5. The problems of machine learning method and their solution
6. Fuzzy logic
7. Text summarization based on fuzzy logic
8. Simulation Results
9. Comparison
10. Conclusion
References
1. Introduction
2. Summarization Approaches
2.1. Statistical Approach
2.2. Linguistic Approach
3. A Review of Text Summarization Based on Machine Learning
4. The Used Attribute in Text Summarization
5. The problems of machine learning method and their solution
6. Fuzzy logic
7. Text summarization based on fuzzy logic
8. Simulation Results
9. Comparison
10. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보