Abstract
The MiTAP prototype for SARS detection uses human language technology for detecting, monitoring, and analyzing potential indicators of infectious disease outbreaks and reasoning for issuing warnings and alerts. MiTAP focuses on providing timely, multilingual information access to analysts, domain experts, and decision-makers worldwide. Data sources are captured, filtered, translated, summarized, and categorized by content. Critical information is automatically extracted and tagged to facilitate browsing, searching, and scanning, and to provide key terms at a glance. The processed articles are made available through an easy-to-use news server and cross-language information retrieval system for access and analysis anywhere, any time. Specialized newsgroups and customizable filters or searches on incoming stories allow users to create their own view into the data while a variety of tools summarize, indicate trends, and provide alerts to potentially relevant spikes of activity.
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CITATION STYLE
Damianos, L. E., Bayer, S., Chisholm, M. A., Henderson, J., Hirschman, L., Morgan, W., … Polyak, M. G. (2004). MiTAP for SARS detection. In HLT-NAACL 2004 - Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Demonstrations (pp. 13–16). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1614025.1614029
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