Arabic medical entity tagging using distant learning
A semantic tagger aiming to detect relevant entities in Arabic medical documents and tagging them with their appropriate semantic class is presented. The system takes profit of a Multilingual Framework covering four languages (Arabic, English, French, and Spanish), in a way that resources available...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2017-04-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157816300854 |
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