Earticle

초록

영어

The study on word similarity computation plays an important role in natural language processing (NLP). Recently the algorithm based on HowNet is widely used and proves to work well in Chinese word similarity computation. However, the relationship between the number of brother nodes and the fineness of the hierarchy is not considered. This paper investigates the ratio of two words on the brother nodes’ number called sememe probability density and proposes an improved algorithm based on HowNet. The results indicate that the correlation measure of the algorithm presented by this paper is 75.4%, and it is much better than the major state-of-the-art method (68.1%).

목차

Abstract
 1. Introduction
 2. Related Work
 3. Algorithm
  3.1 HowNet
  3.2 Similarity between Sememes
  3.3 Similarity between Sets
  3.4 Similarity between Concepts
  3.5 Similarity between words
 4. Evaluation
  4.1 Data Set and Setting
  4.2 Experimental Results
 5. Conclusions
 ACKNOWLEDGEMENTS
 References

키워드

저자

• Rui Zheng [ School of Information Science and Engineering, Hunan University, Changsha, 410082, China ]
• Huan Zhao [ School of Information Science and Engineering, Hunan University, Changsha, 410082, China ]
• Xixiang Zhang [ School of Information Science and Engineering, Hunan University, Changsha, 410082, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605