An ontology-driven system for detecting global health events

Text mining for global health surveillance is an emerging technology that is gaining increased attention from public health organisations and governments. The lack of multilingual resources such as WordNets specifically targeted at this task have so far been a major bottleneck. This paper reports on a major upgrade to the BioCaster Web monitoring system and its freely available multilingual ontology; improving its original design and extending its coverage of diseases from 70 to 336 in 12 languages.

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