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DOTE: Automatic Domain-specific Term Extraction from Wikipedia
WEI Bifan 1 #,LIU Jun 2,MA Jian 2,ZHENG Qinghua 2 *
1.Distant Learning College, Xi'an Jiaotong University
2.School of the Electronic and Information Engineering, Xi'an Jiaotong University
*Correspondence author
#Submitted by
Subject:
Funding: Doctoral Fund of Ministry of Education of China under Grant （No.No. 20130201130002）
Opened online:16 May 2017
Accepted by: none
Citation: WEI Bifan,LIU Jun,MA Jian.DOTE: Automatic Domain-specific Term Extraction from Wikipedia[OL]. [16 May 2017] http://en.paper.edu.cn/en_releasepaper/content/4731848
 
 
Wikipedia contains a large number of domain-specific terms, which can be used in ontology construction, summary generation and other natural language processing tasks. Extracting domain-specific terms automatically is a fundamental task in knowledge acquisition and ontology construction. However, the massive and rapid increasement of domain-specific terms make this task very challenging for conventional rule-based and statistic-based methods. In this paper, we propose an automatic DOmain-specific Term Extraction method (DOTE) from Wikipedia articles. This method is based on three features: (1) the domain focusing of Wikipedia category, (2) domain specificity of Wikipedia revision history and (3) domain indication of first sentence's terms. Our method consists of three stages: (1) generate some domain seed articles from layer 1 according to the domain name; (2) use Feature Voting Model (FVM) to filter domain artilces in layer 1 and 2; (3) expand domain-specific terms from selected categories using subtree expansion. Experimental results show fairly good performance and the practicability of the proposed method.In this paper.
Keywords:Informatica extraction; Domain-specific term extraction; Wikipedia; Hyperlink structure
 
 
 

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