Abstract Hybrid knowledge-based support is based on a combination of following paradigms; Case-based reasoning (CBR), Rule-based reasoning, and several others. CBR is a problem solving paradigm by matching current problem against problems solved successfully in the past. The process can be augmented by adapting solutions. Learning process of a CBR, CBR adaptation can be supported by incorporating adaptation rule bases and data mining methods. This presented research investigates application of CBR and data mining methods on several problem domains. Development of adaptation rule base for CBR adaptation process is also discussed in detail. Framework for integration of data mining methods into CBR is described. This framework is further generalized by incorporating it into Knowledge Discovery Support Environment (KDSE).