MiTAP for SARS detection

  • Authors:

  • Laurie E. Damianos;Samuel Bayer;Michael A. Chisholm;John Henderson;Lynette Hirschman;William Morgan;Marc Ubaldino;Guido Zarrella;James M. Wilson;Marat G. Polyak

  • Affiliations:

  • The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;Georgetown University, Washington, DC;Georgetown University, Washington, DC

  • Venue:
  • HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
  • Year:
  • 2004

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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.