Abstract
Maintenance is generally defined in the field of software and knowledge engineering as an activity that takes place after the development of the system is complete, and the application has already been deployed in operation. The success factor for case-based reasoning (CBR) systems is the quality of their case bases, in order to guarantee this quality, a maintenance process must be planned, and this is how the field of case base maintenance (CBM) emerged. The goal of this paper is to propose a case base maintenance strategy that delivers a small case base size, removes irrelevant cases from the case base, and targets only valuable cases to be retained to increase classification accuracy. We propose a case base maintenance approach C_IRD that focuses on balancing the efficiency of case retrieval and the competence of a case base by employing a soft clustering technique: FCM. The method delivers interesting abilities and is able to maintain case bases with satisfactory accuracy by reducing its size, which leads to a reduction in retrieval time.
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Chebli, A., Djebbar, A., Merouani, H.F. (2022). Case Base Maintenance: Clustering Informative, Representative and Divers Cases (C IRD). In: Ullah, A., Anwar, S., Rocha, Á., Gill, S. (eds) Proceedings of International Conference on Information Technology and Applications. Lecture Notes in Networks and Systems, vol 350. Springer, Singapore. https://doi.org/10.1007/978-981-16-7618-5_34
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DOI: https://doi.org/10.1007/978-981-16-7618-5_34
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