An ontology-driven system for detecting global health events

Nigel Collier; Reiko Matsuda Goodwin; John Mccrae; Son Doan; Ai Kawazoe; Mike Conway; Asanee Kawtrakul; Koichi Takeuchi; Dinh Dien

An ontology-driven system for detecting global health events

Nigel Collier, Reiko Matsuda Goodwin, John Mccrae, Son Doan, Ai Kawazoe, Mike Conway, Asanee Kawtrakul, Koichi Takeuchi, Dinh Dien

Research output: Contribution to conference › Paper › peer-review

29 Scopus citations

Abstract

Text mining for global health surveillance is an emerging technology that is gaining increased attention from public health organizations and governments. The lack of multilingual resources such as Word- Nets specifically targeted at this task has so far been a major bottleneck. This paper reports on a major upgrade to the Bio Caster Web monitoring system and its freely available multilingual ontology; improving its original design and extending its coverage of diseases from 70 to 336 in 12 languages.

Original language	English
Pages	215-222
Number of pages	8
State	Published - 2010
Externally published	Yes
Event	23rd International Conference on Computational Linguistics, Coling 2010 - Beijing, China Duration: Aug 23 2010 → Aug 27 2010

Conference

Conference	23rd International Conference on Computational Linguistics, Coling 2010
Country/Territory	China
City	Beijing
Period	08/23/10 → 08/27/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "An ontology-driven system for detecting global health events",

abstract = "Text mining for global health surveillance is an emerging technology that is gaining increased attention from public health organizations and governments. The lack of multilingual resources such as Word- Nets specifically targeted at this task has so far been a major bottleneck. This paper reports on a major upgrade to the Bio Caster Web monitoring system and its freely available multilingual ontology; improving its original design and extending its coverage of diseases from 70 to 336 in 12 languages.",

author = "Nigel Collier and Goodwin, {Reiko Matsuda} and John Mccrae and Son Doan and Ai Kawazoe and Mike Conway and Asanee Kawtrakul and Koichi Takeuchi and Dinh Dien",

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T1 - An ontology-driven system for detecting global health events

AU - Collier, Nigel

AU - Goodwin, Reiko Matsuda

AU - Mccrae, John

AU - Doan, Son

AU - Kawazoe, Ai

AU - Conway, Mike

AU - Kawtrakul, Asanee

AU - Takeuchi, Koichi

AU - Dien, Dinh

PY - 2010

Y1 - 2010

N2 - Text mining for global health surveillance is an emerging technology that is gaining increased attention from public health organizations and governments. The lack of multilingual resources such as Word- Nets specifically targeted at this task has so far been a major bottleneck. This paper reports on a major upgrade to the Bio Caster Web monitoring system and its freely available multilingual ontology; improving its original design and extending its coverage of diseases from 70 to 336 in 12 languages.

AB - Text mining for global health surveillance is an emerging technology that is gaining increased attention from public health organizations and governments. The lack of multilingual resources such as Word- Nets specifically targeted at this task has so far been a major bottleneck. This paper reports on a major upgrade to the Bio Caster Web monitoring system and its freely available multilingual ontology; improving its original design and extending its coverage of diseases from 70 to 336 in 12 languages.

UR - http://www.scopus.com/inward/record.url?scp=80053390640&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:80053390640

SP - 215

EP - 222

T2 - 23rd International Conference on Computational Linguistics, Coling 2010

Y2 - 23 August 2010 through 27 August 2010

ER -

An ontology-driven system for detecting global health events

Abstract

Conference

UN SDGs

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