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Task aware information access for diagnosis of manufacturing problems
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Source International Conference on Intelligent User Interfaces archive
Proceedings of the 10th international conference on Intelligent user interfaces table of contents
San Diego, California, USA
SESSION: Short papers: knowledge acquisition and knowledge-based design table of contents
Pages: 308 - 310  
Year of Publication: 2005
ISBN:1-58113-894-6
Authors
Larry Birnbaum  Northwestern University, Evanston, IL
Wallace Hopp  Northwestern University, Evanston, IL
Seyed Iravani  Northwestern University, Evanston, IL
Kevin Livingston  Northwestern University, Evanston, IL
Biying Shou  Northwestern University, Evanston, IL
Thomas Tirpak  Realization Research Center Motorola, Schaumburg, IL
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Pinpoint is a promising first step towards using a rich model of task context in proactive and dynamic IR systems. Pinpoint allows a user to navigate decision tree representations of problem spaces, built by domain experts, while dynamically entering annotations specific to their problem. The system then automatically generates queries to information repositories based on both the user's annotations and location in the problem space, producing results that are both task focused and problem specific. Initial feedback from users and domain experts has been positive.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Budzik, J., Hammond K., and Birnbaum, L. 2001. Information access in context. Knowledge-based systems, vol. 14, pp. 37--53.
 
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Hopp, W.J., and Spearman, M.L.. 2000. Factory Physics: Foundations of Manufacturing Management. McGraw-Hill, New York.
 
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Horvitz, E., Jacobs, A., and Hovel, D. 1999. Attention-sensitive alerting. Proc. Conf. on Uncertainty and Artificial Intelligence, pp. 305--313.
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Lieberman, H. 1995. Letizia: An Agent That Assists Web Browsing. The International Joint Conference on Artificial Intelligence.
 
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Rhodes, B. J. and Starner, T. E. 1996. Remembrance agent: A continuously running automated information retrieval system. Practical Applications of Intelligent Agents and Multi-Agent Technology (PAAM).

Collaborative Colleagues:
Larry Birnbaum: colleagues
Wallace Hopp: colleagues
Seyed Iravani: colleagues
Kevin Livingston: colleagues
Biying Shou: colleagues
Thomas Tirpak: colleagues