Abstract
CBET is a software tool for the interactive exploration of a case base. CBET is an integrated environment that provides a range of browsing and display functions that make possible knowledge extraction from a set of cases. CBET is motivated by an application to training firemen. Here cases describe past forest fire fighting interventions and CBET is used to detect dependencies between data, acquire practical planning competences, visualize complex data, clustering similar cases. In CBET well rooted Machine Learning techniques for selecting relevant features, clustering cases and forecasting unknown values have been adapted and reused for case base exploration.
This work has been partially supported by the EspritIV project CARICA #20401 (Cases Acquisition and Replay in Fire Campaign Ambiance).
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© 1997 Springer-Verlag Berlin Heidelberg
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Avesani, P., Perini, A., Ricci, F. (1997). CBET: A Case Base Exploration Tool. In: Lenzerini, M. (eds) AI*IA 97: Advances in Artificial Intelligence. AI*IA 1997. Lecture Notes in Computer Science, vol 1321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63576-9_126
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DOI: https://doi.org/10.1007/3-540-63576-9_126
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