원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.2
2016.02
pp.17-22
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Word sense disambiguation (WSD) plays an important role in natural language processing fields. Semantic category is semantic knowledge and part-of-speech is syntax knowledge. In this paper, word window is opened to get semantic category and part-of-speech of left and right adjacent words around an ambiguous word. A new approach of determining true meanings of ambiguous words based on support vector machine (SVM) is given. The training corpus in SemEval-2007: Task#5 is applied to optimize SVM and the optimized SVM is tested. Experimental results show that the performance of the proposed method is improved.
목차
Abstract
1. Introduction
2. Extracting Part-of-Speech and Semantic Information
3. Word Sense Disambiguation Classifier Based on SVM
4. Experiments
5. Conclusion
Acknowledgement
References
1. Introduction
2. Extracting Part-of-Speech and Semantic Information
3. Word Sense Disambiguation Classifier Based on SVM
4. Experiments
5. Conclusion
Acknowledgement
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보