Title :
Automatic Case Generation for Case-Based Reasoning Systems Using Genetic Algorithms
Author :
Manzoor, J. ; Asif, Shahidul ; Masud, M. ; Khan, M. Jawad
Author_Institution :
Dept. of Comput. Sci., Kinnaird Coll. for Women, Lahore, Pakistan
Abstract :
Case-Based Reasoning (CBR) has been employed as a problem-solving technique to solve numerous real-world applications. At the core of a successful CBR system is a high-quality case-base. Generating a quality case-base with minimal human intervention is a significant challenge which has not been given considerable attention in the past. In this paper, we propose a methodology for automatic generation of a quality case-base using genetic algorithm (GA). GA has been effectively used to evaluate quality of cases using predefined criteria as part of the fitness function. The performance and efficiency of the proposed approach has been evaluated and presented on the examination scheduling problem.
Keywords :
case-based reasoning; educational administrative data processing; genetic algorithms; performance evaluation; problem solving; CBR system; GA; automatic case generation; case quality evaluation; case-based reasoning systems; efficiency evaluation; examination scheduling problem; fitness function; genetic algorithms; high-quality case-based system; performance evaluation; problem solving technique; Biological cells; Cognition; Expert systems; Genetic algorithms; Maintenance engineering; Schedules; Sociology;
Conference_Titel :
Intelligent Systems (GCIS), 2012 Third Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4673-3072-5
DOI :
10.1109/GCIS.2012.89