Abstract
Case-Based Reasoning (CBR) systems solve new problems using others which have been previously resolved in a case memory, where each case represents a solved situation. Therefore, the case memory size and its organization influences on the computational time needed to solve new situations. For this reason, we organize the memory using a Self-Organization Map for defining patterns to allow system to do a selective retrieval using only the cases of the most suitable pattern. This works presents a case-based maintenance to incrementally introduce knowledge in SOM without retraining it because this process is very expensive in terms of computational time. The strategy is semi-supervised because we use the feedback provided by the expert and, at the same time, the self-organization of cases when clusters are readjusted. Results show a successful case-based maintenance.
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Fornells, A., Golobardes, E. (2007). Case-Base Maintenance in an Associative Memory Organized by a Self-Organization Map. In: Corchado, E., Corchado, J.M., Abraham, A. (eds) Innovations in Hybrid Intelligent Systems. Advances in Soft Computing, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74972-1_41
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DOI: https://doi.org/10.1007/978-3-540-74972-1_41
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