Abstract
Public health surveillance systems rely on the automated monitoring of large amounts of text. While building a text mining system for veterinary syndromic surveillance, we exploit automatic and semi-automatic methods for terminology construction at different stages. Our approaches include term extraction from free-text, grouping of term variants based on string similarity, and linking to an existing medical ontology.
| Original language | English |
|---|---|
| Title of host publication | CEUR Workshop Proceedings |
| Pages | 61-70 |
| Number of pages | 10 |
| Volume | 1495 |
| Publication status | Print publication - 2015 |
| Externally published | Yes |
| Event | 11th International Conference on Terminology and Artificial Intelligence, TIA 2015 - Granada, Spain Duration: 4 Nov 2015 → 6 Nov 2015 |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Publisher | CEUR Workshop Proceedings |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | 11th International Conference on Terminology and Artificial Intelligence, TIA 2015 |
|---|---|
| Country/Territory | Spain |
| City | Granada |
| Period | 4/11/15 → 6/11/15 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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