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User studies of an interdependency-based interface for acquiring problem-solving knowledge
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Source International Conference on Intelligent User Interfaces archive
Proceedings of the 5th international conference on Intelligent user interfaces table of contents
New Orleans, Louisiana, United States
Pages: 165 - 168  
Year of Publication: 2000
ISBN:1-58113-134-8
Authors
Jihie Kim  USC/Information Sciences Institute, 4676 Admiralty Way, Marina del Rey, CA
Yolanda Gil  USC/Information Sciences Institute, 4676 Admiralty Way, Marina del Rey, CA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 1,   Downloads (12 Months): 14,   Citation Count: 3
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ABSTRACT

This paper describes a series of experiments with a range of users to evaluate an intelligent interface for acquiring problem-solving knowledge to describe how to accomplish a task. The tool derives the interdependencies between different pieces of knowledge in the system and uses them to guide the user in completing the acquisition task. The paper describes results obtained when the tool was tested with a wide range of users, including end users. The studies show that our acquisition interface saves users an average of 32% of the time it takes to add new knowledge, and highlight some interesting differences across user groups. The paper also describes what are the areas that need to be addressed in future research in order to make these tools usable by end users.


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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Cohen, P., Schrag, R., Jones, E., Pease, A., Lin, A., Starr, B., Gunning, D., and Burke, M. (lYY8). The DARPA High- Performance Knowledge Bases project. AI Magazine, 19(4).
 
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Gil, Y. and Melz, E. (1996) Explicit representations of problemsolving strategies to support knowledge acquisition. In Proceedings of AAAI-96.
 
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GUI, Y. (lYY4) Knowledge retmement m a re~lectlve architecture. In Proceedings of AAAI-94.
 
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Mitchell, T., Mahadevan, S. and Steinberg, L. (1982) LEAP: A learning apprentice for VLSI design. In Proceedings of IJCAI-85.
 
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Tallis, M., Kim, J. and Gil, Y. (1999) User studies of knowledge acquisition tools: Methodology and lessons learned. In Proceedings of KAW-99.
 
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Swartout B. and Gil, Y. (1995) EXPECT: Explicit representations for flexible acquisition. In Proceedings of KAW-95.



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