An adaptive CBR model of call center systems

Adaptation is one of the necessary capabilities of any expert system. In a traditional expert system, the evolving environment is often treated in a static view. And the system accepts the change negatively. Our focus in this paper is to construct an adaptive CBR model which can learn continually through detecting feedbacks from the outside to partially release this. Knowledge base here is improved gradually so to enhance the system´s adaptation of solving problems in dynamic environment.