Maintenance of Case Bases: Current Algorithms After Fifty Years
Abstract
Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from model-based systems since it can learn incrementally as new data is available, storing new cases in its case-base. 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.
Cite
Text
Juarez et al. "Maintenance of Case Bases: Current Algorithms After Fifty Years." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/770Markdown
[Juarez et al. "Maintenance of Case Bases: Current Algorithms After Fifty Years." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/juarez2018ijcai-maintenance/) doi:10.24963/IJCAI.2018/770BibTeX
@inproceedings{juarez2018ijcai-maintenance,
title = {{Maintenance of Case Bases: Current Algorithms After Fifty Years}},
author = {Juarez, Jose M. and Craw, Susan and Lopez-Delgado, J. Ricardo and Campos, Manuel},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {5457-5463},
doi = {10.24963/IJCAI.2018/770},
url = {https://mlanthology.org/ijcai/2018/juarez2018ijcai-maintenance/}
}