Earticle

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

키워드

저자

• Zhang Chun-Xiang [ School of Software, Harbin University of Science and Technology, Harbin 150080, China, College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China ]
• Sun Lu-Rong [ School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ]
• Gao Xue-Yao [ School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605