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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 the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639299/ https://www.ncbi.nlm.nih.gov/pubmed/18922806 http://dx.doi.org/10.1093/bioinformatics/btn534 |
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author | Collier, Nigel Doan, Son Kawazoe, Ai Goodwin, Reiko Matsuda Conway, Mike Tateno, Yoshio Ngo, Quoc-Hung Dien, Dinh Kawtrakul, Asanee Takeuchi, Koichi Shigematsu, Mika Taniguchi, Kiyosu |
author_facet | Collier, Nigel Doan, Son Kawazoe, Ai Goodwin, Reiko Matsuda Conway, Mike Tateno, Yoshio Ngo, Quoc-Hung Dien, Dinh Kawtrakul, Asanee Takeuchi, Koichi Shigematsu, Mika Taniguchi, Kiyosu |
author_sort | Collier, Nigel |
collection | PubMed |
description | 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. Contact: collier@nii.ac.jp |
format | Text |
id | pubmed-2639299 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-26392992009-02-25 BioCaster: detecting public health rumors with a Web-based text mining system Collier, Nigel Doan, Son Kawazoe, Ai Goodwin, Reiko Matsuda Conway, Mike Tateno, Yoshio Ngo, Quoc-Hung Dien, Dinh Kawtrakul, Asanee Takeuchi, Koichi Shigematsu, Mika Taniguchi, Kiyosu Bioinformatics Applications Note 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. Contact: collier@nii.ac.jp Oxford University Press 2008-12-15 2008-10-15 /pmc/articles/PMC2639299/ /pubmed/18922806 http://dx.doi.org/10.1093/bioinformatics/btn534 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Collier, Nigel Doan, Son Kawazoe, Ai Goodwin, Reiko Matsuda Conway, Mike Tateno, Yoshio Ngo, Quoc-Hung Dien, Dinh Kawtrakul, Asanee Takeuchi, Koichi Shigematsu, Mika Taniguchi, Kiyosu BioCaster: detecting public health rumors with a Web-based text mining system |
title | BioCaster: detecting public health rumors with a Web-based text mining system |
title_full | BioCaster: detecting public health rumors with a Web-based text mining system |
title_fullStr | BioCaster: detecting public health rumors with a Web-based text mining system |
title_full_unstemmed | BioCaster: detecting public health rumors with a Web-based text mining system |
title_short | BioCaster: detecting public health rumors with a Web-based text mining system |
title_sort | biocaster: detecting public health rumors with a web-based text mining system |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639299/ https://www.ncbi.nlm.nih.gov/pubmed/18922806 http://dx.doi.org/10.1093/bioinformatics/btn534 |
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