Document classification toward efficient event-based biosurveillance

Description: 

Event-based biosurveillance is a practice of monitoring diverse information sources for the detection of events pertaining to human health. Online documents, such as news articles on the Internet, have commonly been the primary information sources in event-based biosurveillance. With the large number of online publications as well as with the language diversity, thorough monitoring of online documents is challenging. Automated document classification is an important step toward efficient event-based biosurveillance. In Project Argus, a biosurveillance program hosted at Georgetown University Medical Center, supervised and unsupervised approaches to document classification are considered for event-based biosurveillance.

 

Objective

This paper describes ongoing efforts in enhancing automated document classification toward efficient event-based biosurveillance. 

Primary Topic Areas: 
Original Publication Year: 
2010
Event/Publication Date: 
December, 2010

June 14, 2019

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