Abstract
Human-centered computing studies methods to improve the interactions and performance of combined human/machine systems. Case-based reasoning provides a natural method for supporting knowledge capture and access in such systems. However, the human-centered approach raises numerous questions about how best to address variations in individual human needs. These questions include how to reflect individual perspectives, how to adjust to changing task contexts, and how each part of the combined system can help to extend the capabilities of the other. This talk describes ongoing research addressing these questions in the context of case-based support for human knowledge modeling and construction.
This research is supported in part by NASA under award No NCC 2-1216. It is done in collaboration with Ana Maguitman and Thomas Reichherzer of Indiana University and with Alberto Cañas and the concept mapping group of The Institute for Human and Machine Cognition, at the University of West Florida.
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© 2003 Springer-Verlag Berlin Heidelberg
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Leake, D.B. (2003). Human-Centered CBR: Integrating Case-Based Reasoning with Knowledge Construction and Extension. In: Ashley, K.D., Bridge, D.G. (eds) Case-Based Reasoning Research and Development. ICCBR 2003. Lecture Notes in Computer Science(), vol 2689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45006-8_1
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DOI: https://doi.org/10.1007/3-540-45006-8_1
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