BioCaster: detecting public health rumors with a Web-based text mining system.

SUMMARY: BioCaster is an ontology-based text mining system for detecting and tracking the distribution of infectious disease outbreaks from linguistic signals on the Web. The system continuously analyzes documents reported from over 1700 RSS feeds, classifies them for topical relevance and plots them onto a Google map using geocoded information. The background knowledge for bridging the gap between Layman's terms and formal-coding systems is contained in the freely available BioCaster ontology which includes information in eight languages focused on the epidemiological role of pathogens 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 event recognition. Higher order event analysis is used to detect more precisely specified warning signals that can then be notified to registered users via email alerts. Evaluation of the system for topic recognition and entity identification is conducted on a gold standard corpus of annotated news articles. AVAILABILITY: The BioCaster map and ontology are freely available via a web portal at http://www.biocaster.org.

A multilingual ontology for infectious disease surveillance: rationale, design and challenges.

A lack of surveillance system infrastructure in the Asia-Pacific region is seen as hindering the global control of rapidly spreading infectious diseases such as the recent avian H5N1 epidemic. As part of improving surveillance in the region, the BioCaster project aims to develop a system based on text mining for automatically monitoring Internet news and other online sources in several regional languages. At the heart of the system is an application ontology which serves the dual purpose of enabling advanced searches on the mined facts and of allowing the system to make intelligent inferences for assessing the priority of events. However, it became clear early on in the project that existing classification schemes did not have the necessary language coverage or semantic specificity for our needs. In this article we present an overview of our needs and explore in detail the rationale and methods for developing a new conceptual structure and multilingual terminological resource that focusses on priority pathogens and the diseases they cause. The ontology is made freely available as an online database and downloadable OWL file.