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논문검색

Word Sense Disambiguation Based on Perceptron Model

원문정보

Zhang Chun-Xiang, Gao Xue-Yao, Lu Zhi-Mao

보안공학연구지원센터(IJDTA) International Journal of Database Theory and Application Vol.9 No.5 2016.05 pp.121-128
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초록

영어

Word sense disambiguation (WSD) is an important research topic in natural language processing field, which is very useful for machine translation and information retrieval. In this paper, a linear combination model based on multiple discriminative features is proposed to determine correct sense of an ambiguous word, in which morphology and part of speech in left and right words around ambiguous word are used as features. Then, perceptron algorithm is applied to optimize the WSD model. Experiments show that the WSD performance is improved after the proposed method is applied.

목차

Abstract
 1. Introduction
 2. Discriminative Features in WSD Model
 3. WSD Classifier Based on Perceptron Algorithm
 4. Experiments
 5. Conclusion
 Acknowledgements
 References

키워드

저자정보

  • Zhang Chun-Xiang College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China, School of Software, 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
  • Lu Zhi-Mao School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China

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