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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...

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Autores principales: 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
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
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
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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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