  We present the Global Health Monitor, an online Web-based system for
detecting and mapping infectious disease outbreaks that appear in news stories.
The system analyzes English news stories from news feed providers, classifies
them for topical relevance and plots them onto a Google map using geo-coding
information, helping public health workers to monitor the spread of diseases in
a geo-temporal context. The background knowledge for the system is contained in
the BioCaster ontology (BCO) (Collier et al., 2007a) which includes both
information on infectious diseases as well as geographical locations with their
latitudes/longitudes. The system consists of four main stages: topic
classification, named entity recognition (NER), disease/location detection and
visualization. Evaluation of the system shows that it achieved high accuracy on
a gold standard corpus. The system is now in practical use. Running on a
clustercomputer, it monitors more than 1500 news feeds 24/7, updating the map
every hour.
