Identification

Author

Collier N, Doan S, Kawazoe A, Goodwin RM, Conway M, et al.

Title

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

Year

2008

Publication type

Article

Journal

Bioinformatics

Modified

2016-06-30 20:43:54.052002+00:00

Details

Volume

24

Number

24

Access

Language

English

URL http://bioinformatics.oxfordjournals.org/content/24/24/2940.abstract
DOI

10.1093/bioinformatics/btn534

Accessed

2016-04-26

Extended information

Abstract

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.Contact: collier@nii.ac.jp