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New Technology of Library and Information Service  2008, Vol. 24 Issue (9): 36-40    DOI: 10.11925/infotech.1003-3513.2008.09.06
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Ontoloy Relationship Extraction Research Based on HowNet and Term Relevancy Degree
Fu JibinLiu JieJia KeliangMao Jintao1
1(School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China)
2 (School of Information Engineering, Capital Normal University, Beijing 100037, China)
3 (School of Information Management, Shandong Economic University, Jinan 250014, China)
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Abstract  

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.

Key wordsRelationship extraction      Ontology learning      HowNet      NLP     
Received: 19 June 2008      Published: 25 September 2008
: 

TP391

 
Corresponding Authors: Fu Jibin     E-mail: fujibin@gmail.com
About author:: Fu Jibin,Liu Jie,Jia Keliang,Mao Jintao

Cite this article:

Fu Jibin,Liu Jie,Jia Keliang,Mao Jintao. Ontoloy Relationship Extraction Research Based on HowNet and Term Relevancy Degree. New Technology of Library and Information Service, 2008, 24(9): 36-40.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2008.09.06     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2008/V24/I9/36

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