Extended Experimental Explorations of the Necessity of User Guidance in Case-Based Learning

This is an extended report focussing on experimen-tal results to explore the necessity of user guidance in case-based knowledge acquisition. It is covering a collection of theoretical investigations as well. The methodology of our approach is quite simple: We choose a well-understood area which is tailored to case-based knowledge acquisition. Furthermore, we choose a prototypical case-based learning algorithm which is obviously suitable for the problem domain under consideration. Then, we perform a number of knowledge acquisition experiments. They clearly exhibit essential limitations of knowledge acquisition from randomly chosen cases. As a consequence, we develop scenarios of user guidance. Based on these theoretical concepts, we prove a few theoretical re-sults characterizing the power of our approach. Next, we perform a new series of more constrained results which support our theoretical investigations. The main experiments deal with the diculties of learning from randomly arranged data in 4 dierent formal settings. The key insight is that even the right data do not suce, if they are not arranged appro-priately. The present report aims at presenting a large amount of experimental data exceeding the space available in conference proceedings, usually. We are reporting more than a million of individual learning experiments, each of them comprising several steps Part of this work has been supported by the German Re