Title :
Domain knowledge acquisition by automatic semantic annotating and pattern mining
Author :
Hao, Tianyong ; Qu, Yingying ; Xia, Fang
Author_Institution :
Dept. of Chinese, Translation & Linguistics, City Univ. of Hong Kong, Hong Kong, China
Abstract :
Manual knowledge acquisition is extremely laborious and time consuming. In this paper, we propose a new automatic method for domain knowledge acquisition by semantic annotating and pattern mining. This method makes use of Minipar to label sentences and extract structural patterns. Semantic bank is proposed to annotate and represent concepts with semantic labels considering sentence context. The method can further learn and assign relations to previously extracted concepts by pattern matching. The involved concepts and semantic labels with learned relations together construct a domain knowledge base. Preliminary experiments on Yahoo! Data in “heart diseases” category show that this method is feasible for automatic domain knowledge acquisition.
Keywords :
cardiology; data mining; diseases; knowledge based systems; medical computing; pattern matching; Minipar; Yahoo! Data; automatic method; automatic semantic annotation; domain knowledge acquisition; domain knowledge base; heart diseases; pattern matching; pattern mining; semantic bank; semantic labels; sentence context; sentence labeling; structural pattern extraction; Context; Data mining; Knowledge acquisition; Knowledge based systems; OWL; Pattern matching; Semantics; knowledge acqistion; semantic annotation; semantic bank; structural pattern; transform rule;
Conference_Titel :
Information Retrieval & Knowledge Management (CAMP), 2012 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-1091-8
DOI :
10.1109/InfRKM.2012.6205009