A New Semantic Similarity Measurement Based on HowNet Concept Tree
Authors
Xiaohua Guo, Xinhua Zhu, Fei Li, Qi Li
Corresponding Author
Xiaohua Guo
Available Online January 2016.
- DOI
- 10.2991/ifmeita-16.2016.132How to use a DOI?
- Keywords
- Concept Tree, HowNet, Semantic Similarity, Path, Depth.
- Abstract
This paper puts forward a new depth & path-based semantic similarity method to improve the existing meaning-based approaches in HowNet. Firstly, a complete concept tree is constructed on the sememe tree according to the concept definitions in HowNet. Then an improved depth & path algorithm was put forward, in which five adjustable parameters are used to compute the depth and path of concept in concept tree. This method avoids the computation process of complicated meaning similarity and is more intuitive and efficient. The experiment shows that proposed algorithm has achieved an excellent level comparing with the existing word similarity algorithms.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaohua Guo AU - Xinhua Zhu AU - Fei Li AU - Qi Li PY - 2016/01 DA - 2016/01 TI - A New Semantic Similarity Measurement Based on HowNet Concept Tree BT - Proceedings of the 2016 International Forum on Management, Education and Information Technology Application PB - Atlantis Press SP - 722 EP - 727 SN - 2352-5398 UR - https://doi.org/10.2991/ifmeita-16.2016.132 DO - 10.2991/ifmeita-16.2016.132 ID - Guo2016/01 ER -