DocumentCode :
2282357
Title :
The Building of a CBD-Based Domain Ontology in Chinese
Author :
Sui, Zhifang ; Zhao, Jun ; Kang, Wei ; Zhao, Qingliang
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Peking
Volume :
3
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
303
Lastpage :
306
Abstract :
This paper describes a method of building a medical ontology prototype in Chinese. During the procedure, we explored the following questions, which are crucial for the task of ontology engineering: (1) are there some more computer-understandable knowledge description models? We proposed a structural and fine-grained knowledge description model called concept-based description model (CBD) to describe the rich knowledge in the ontology. That is, to use other concept or the combination of the related concepts to represent the targeted concept, which is supposed to be more computer-understandable; (2) during large scale ontology engineering, how to use NLP technologies to reduce domain expertspsila work to the minimal? In our work, we used some NLP technologies to try to reduce domain expertspsila work to the minimal as possible as it can. The experiments show the significance of our method.
Keywords :
medical computing; natural language processing; ontologies (artificial intelligence); Chinese language; NLP technology; computer-understandable knowledge description model; concept-based description model; domain ontology building; medical ontology; ontology engineering; Biomedical engineering; Buildings; Computational linguistics; Computer science; Design engineering; Intelligent agent; Knowledge engineering; Large-scale systems; Natural languages; Ontologies; domain ontology; knowledge organization; natural language processing; term extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.183
Filename :
4740785
Link To Document :
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