%A Fu Jibin,Liu Jie,Jia Keliang,Mao Jintao %T Ontoloy Relationship Extraction Research Based on HowNet and Term Relevancy Degree %0 Journal Article %D 2008 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2008.09.06 %P 36-40 %V 24 %N 9 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_640.shtml} %8 2008-09-25 %X

The paper proposes a relationship extraction method based on HowNet and term relevancy degree. Firstly syntax parsing tools are used to extract context feature of terms, and natural language feature and statistical mutual information measure are integrated to compute relevancy degree of terms,then dynamic role and sememe are used as key to seek the relationship in HowNet semantic relationship framework, and explicit semantic lable is designated to the relationship. Experimental results show that the approach is effective.