A refined model of ontology-driven information extraction
Chunyu Cong, Shan Huo, Xiao Meng, Rui Gao, Zhongying Wang
Available Online January 2017.
- 10.2991/icmmita-16.2016.110How to use a DOI?
- Ontology; information extraction
An ontology is a formal and normalized explanation of a shared conceptualization while information extraction (IE) is a form of natural language processing in which certain types of information must be recognized and extracted from text. The methods of ontology-based IE fall in two broad categories: document-driven IE and ontology-driven IE. Document-driven IE is known as semantic annotation which annotates and manages the knowledge in semantic web with the semantic information in domain ontologies. Ontology-driven IE can extract information from unstructured documents based on a domain ontology. In this paper, we use ontology-driven IE to extract hazard information from Chinese food complaint documents and the results are delightful.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Chunyu Cong AU - Shan Huo AU - Xiao Meng AU - Rui Gao AU - Zhongying Wang PY - 2017/01 DA - 2017/01 TI - A refined model of ontology-driven information extraction BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 591 EP - 594 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.110 DO - 10.2991/icmmita-16.2016.110 ID - Cong2017/01 ER -