Abstract
Animal diseases-related news articles are richin information useful for risk assessment. In this paper, we explore a method to automatically retrieve sentence-level epidemiological information. Our method is an incremental approach to create and expand patterns at both lexical and syntactic levels. Expert knowledge input are used at different steps of the approach. Distributed vector representations (word embedding) were used to expand the patterns at the lexical level, thus alleviating manual curation. We showed that expert validation was crucial to improve the precision of automatically generated patterns.- Anthology ID:
- 2020.louhi-1.8
- Volume:
- Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- Louhi
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 70–78
- Language:
- URL:
- https://aclanthology.org/2020.louhi-1.8
- DOI:
- 10.18653/v1/2020.louhi-1.8
- Cite (ACL):
- Sarah Valentin, Mathieu Roche, and Renaud Lancelot. 2020. Information retrieval for animal disease surveillance: a pattern-based approach.. In Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis, pages 70–78, Online. Association for Computational Linguistics.
- Cite (Informal):
- Information retrieval for animal disease surveillance: a pattern-based approach. (Valentin et al., Louhi 2020)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2020.louhi-1.8.pdf