Using hedges to enhance a disease outbreak report text mining system

Authors:
Mike Conway;Nigel Collier;Son Doan
Affiliations:
National Institute of Informatics, Chiyoda-ku, Tokyo, Japan;National Institute of Informatics, Chiyoda-ku, Tokyo, Japan;Vanderbilt University Medical Center, Nashville, TN
Venue:
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Year:
2009

Citing 2
Cited 4

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Abstract

Identifying serious infectious disease outbreaks in their early stages is an important task, both for national governments and international organizations like the World Health Organization. Text mining and information extraction systems can provide an important, low cost and timely early warning system in these circumstances by identifying the first signs of an outbreak automatically from online textual news. One interesting characteristic of disease outbreak reports --- which to the best of our knowledge has not been studied before --- is their use of speculative language (hedging) to describe uncertain situations. This paper describes two uses of hedging to enhance the BioCaster disease outbreak report text mining system.