Article

MiTAP for real users, real data, real problems

Authors:

Laurie Damianos,

Steve Wohlever,

Robyn Kozierok,

Jay PonteAuthors Info & Claims

CHI EA '03: CHI '03 Extended Abstracts on Human Factors in Computing Systems

Pages 656 - 657

https://doi.org/10.1145/765891.765913

Published: 05 April 2003 Publication History

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Abstract

The MiTAP system was developed as an experimental prototype using human language technologies for monitoring disease outbreaks. The system provides timely, multi-lingual, global information access to analysts, medical experts and individuals involved in humanitarian assistance. Thousands of articles from electronic information sources spanning multiple languages are automatically captured, translated, tagged, summarized, and presented to users in a variety of ways. Real users access MiTAP daily to solve real problems. The successful adoption of MiTAP is attributed to its user-focused design that accommodates the imperfect component technologies and allows users to interact with the system in familiar ways. We will discuss the problem, design process, and implementation from the perspective of services provided and how these services support system capabilities that satisfy user requirements.

References

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Alias I, Inc, 2002. New Technology for Information Access. http://www.alias-i.com]]

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Columbia Newsblaster, 2002. http://www.cs.columbia.edu/nlp/newsblaster]]

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MiTAP System 2001, http://tides2000.mitre.org/.]]

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Vilain, M. 1999. Inferential Information Extraction in Pazienza, M., ed., Information Extraction, Lecture notes of the 1999 SCIE Summer School on Information Extraction, ed. M. Pazienza, 95--119. Springer Verlag.]]

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Cited By

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Burger JFerro LDolan BDagan I(2005)Generating an entailment corpus from news headlinesProceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment10.5555/1631862.1631871(49-54)Online publication date: 30-Jun-2005
https://dl.acm.org/doi/10.5555/1631862.1631871
Bayer SBurger JFerro LHenderson JHirschman LYeh A(2005)Evaluating semantic evaluationsProceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment10.1007/11736790_18(309-331)Online publication date: 11-Apr-2005
https://dl.acm.org/doi/10.1007/11736790_18

MiTAP for real users, real data, real problems
1. Human-centered computing
  1. Interaction design
    1. Interaction design process and methods

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Published In

CHI EA '03: CHI '03 Extended Abstracts on Human Factors in Computing Systems

April 2003

471 pages

ISBN:1581136374

DOI:10.1145/765891

Conference Chairs:
Gilbert Cockton
University of Sunderland, UK
,
Panu Korhonen
Nokia Research Center, Finland

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 April 2003

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CHI03

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CHI03: Human Factors in Computing Systems

April 5 - 10, 2003

Florida, Ft. Lauderdale, USA

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Burger JFerro LDolan BDagan I(2005)Generating an entailment corpus from news headlinesProceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment10.5555/1631862.1631871(49-54)Online publication date: 30-Jun-2005
https://dl.acm.org/doi/10.5555/1631862.1631871
Bayer SBurger JFerro LHenderson JHirschman LYeh A(2005)Evaluating semantic evaluationsProceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment10.1007/11736790_18(309-331)Online publication date: 11-Apr-2005
https://dl.acm.org/doi/10.1007/11736790_18

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Real users, real data, real problems: the MiTAP system for monitoring bio events

An infrastructure for real-time population health assessment and monitoring

Real Time Remote Diagnosis and Distant Education using CollabDDS