Abstract
The human behavior has always been very influential in systems engineering. In fact, AI methods and techniques are largely influenced by the human behavior in the form of mental and mechanical capabilities. The human learning, persevering and then recalling knowledge is the focal point in artificial intelligence research. But less attention is paid to forgetting as one of the characteristics that have a very positive role in human intelligence. This paper seeks to integrate data forgetting as part of the behavior of case-based reasoning systems. The aim is to improve the performance of CBR systems by filtering out irrelevant cases as part of the machine behavior in the form of CBR systems. The paper presents a prototypical implementation of the of a forgettable CBR system that provides course recommendations as part of student registration system. Experimental work has been carried out using historical data of postgraduate students in the Computer science department, Tripoli University, Libya. Keywords: Knowledge management, CBR, machine forgetting, recommendation systems.