Hybrid approach for case adaptation

When Case Based Reasoning systems are applied to real-world problems, the retrieved solutions in general require adaptations in order to be used on new contexts. Therefore, case adaptation is a desirable capability. However, case adaptation is still a challenge for this research area. In general, the the achievement of knowledge for case adaptation is harder than acquisition of cases. This paper proposes a hybrid approach for case adaptation able to learn adaptation knowledge from a Case Base.