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. © 2012 IEEE.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12 |
| Pages | 34-38 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12 - Kuala Lumpur, Malaysia Duration: 13 Mar 2012 → 15 Mar 2012 |
Conference
| Conference | 2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12 |
|---|---|
| Place | Malaysia |
| City | Kuala Lumpur |
| Period | 13/03/12 → 15/03/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- knowledge acqistion
- semantic annotation
- semantic bank
- structural pattern
- transform rule
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