Abstract:  Case-Based Reasoning (CBR) is the process of solving problems by properly adapting the solutions of similar (analogous) problems solved in the past. As an Artificial Intelligence’s method CBR has become recently very popular to information managers increasing the effectiveness and reducing the cost of various human activities by substantially automated processes, such as diagnosis, scheduling, design, etc. In this paper a combination is utilized of the Centre of Gravity defuzzification technique and of the Fuzzy Numbers for assessing the effectiveness of CBR systems. Our new fuzzy assessment approach is validated by comparing its outcomes in our applications with the corresponding outcomes of two traditional assessment methods, the calculation of the mean values and the GPA index.

Keywords: Analogical Reasoning (AR), Case-Based Reasoning (CBR), Fuzzy Logic (FL), Centre of Gravity (COG) Defuzzification Technique, Triangular and Trapezoidal Fuzzy Numbers (TFNs and TpFNs), GPA index.