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Domain knowledge acquisition by automatic semantic annotating and pattern mining

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3 Author(s)
Tianyong Hao ; Department of Chinese, Translation and Linguistics, City University of Hong Kong, Hong Kong ; Yingying Qu ; Fang Xia

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.

Published in:

Information Retrieval & Knowledge Management (CAMP), 2012 International Conference on

Date of Conference:

13-15 March 2012