BioCaster: detecting public health rumors with a Web-based text mining system.
Bioinformatics
; 24(24): 2940-1, 2008 Dec 15.
Article
em En
| MEDLINE
| ID: mdl-18922806
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Vigilância da População
/
Armazenamento e Recuperação da Informação
Tipo de estudo:
Prognostic_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2008
Tipo de documento:
Article
País de afiliação:
Japão