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Maintenance of case bases: current algorithms after fifty years.

Juarez, Jose M.; Craw, Susan; Lopez-Delgado, J. Ricardo; Campos, Manuel


Jose M. Juarez

J. Ricardo Lopez-Delgado

Manuel Campos


Jérôme Lang


Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from modelbased systems since it can learn incrementally as new data is available, storing new cases in its casebase. This means that it can benefit from readily available new data, but also case-base maintenance (CBM) is essential to manage the cases, deleting and compacting the case-base. In the 50th anniversary of CNN (considered the first CBM algorithm), new CBM methods are proposed to deal with the new requirements of Big Data scenarios. In this paper, we present an accessible historic perspective of CBM and we classify and analyse the most recent approaches to deal with these requirements.

Start Date Jul 13, 2018
Publication Date Jul 19, 2018
Print ISSN 1045-0823
Publisher IJCAI
Pages 5457-5463
Series ISSN 1045-0823
Institution Citation JUAREZ, J.M., CRAW, S., LOPEZ-DELGADO, J.R. and CAMPOS, M. 2018. Maintenance of case bases: current algorithms after fifty years. In Lang, J. (ed.) Proceedings of the 27th International joint conference on artificial intelligence and the 23rd European conference on artificial intelligence (IJCAI-ECAI 2018), 13-19 July 2018, Stockholm, Sweden. Freiburg: IJCAI [online], pages 5457-5463. Available from:
Keywords Case based reasoning; CBR; Case based maintenance; Algorithms


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