Global Health Monitor: A Web-based System for Detecting and Mapping Infectious Diseases

November 21, 2019 Β· Declared Dead Β· πŸ› International Joint Conference on Natural Language Processing

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Authors Son Doan, Quoc-Hung Ngo, Ai Kawazoe, Nigel Collier arXiv ID 1911.09735 Category cs.IR: Information Retrieval Cross-listed cs.CL, cs.CY Citations 42 Venue International Joint Conference on Natural Language Processing Last Checked 4 months ago
Abstract
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.
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