Case Base Mining for Adaptation Knowledge Acquisition

d&apos;Aquin, Mathieu; Badra, Fadi; Lafrogne, Sandrine; Lieber, Jean; Napoli, Amedeo; Szathmary, Laszlo

Case Base Mining for Adaptation Knowledge Acquisition

Mathieu d'Aquin, Fadi Badra, Sandrine Lafrogne, Jean Lieber, Amedeo Napoli, Laszlo Szathmary

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Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 750-754.

Abstract

In case-based reasoning, the adaptation of a source case in order to solve the target problem is at the same time crucial and difficult to implement. The reason for this difficulty is that, in general, adaptation strongly depends on domain-dependent knowledge. This fact motivates research on adaptation knowledge acquisition (AKA). This paper presents an approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining. It is implemented in CabamakA, a system that explores the variations within the case base to elicit adaptation knowledge. This system has been successfully tested in an application of case-based reasoning to decision support in the domain of breast cancer treatment.

Mathieu d'Aquin, Fadi Badra, Sandrine Lafrogne, Jean Lieber, Amedeo Napoli, and Laszlo Szathmary. 2007. Case Base Mining for Adaptation Knowledge Acquisition. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07. IJCAI, 750–754. https://ijcai.org/proceedings/2007/120

@inproceedings{ijcai2007p120,
  title     = {Case Base Mining for Adaptation Knowledge Acquisition},
  author    = {d&apos;Aquin, Mathieu and Badra, Fadi and Lafrogne, Sandrine and Lieber, Jean and Napoli, Amedeo and Szathmary, Laszlo},
  booktitle = {Proceedings of the Twentieth International Joint Conference on
               Artificial Intelligence, {IJCAI-07}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Ramon López de Mántaras},
  pages     = {750--754},
  year      = {2007},
  url       = {https://ijcai.org/proceedings/2007/120},
}

TY  - CPAPER
TI  - Case Base Mining for Adaptation Knowledge Acquisition
AU  - d&apos;Aquin, Mathieu
AU  - Badra, Fadi
AU  - Lafrogne, Sandrine
AU  - Lieber, Jean
AU  - Napoli, Amedeo
AU  - Szathmary, Laszlo
T2  - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2007
SP  - 750
EP  - 754
UR  - https://ijcai.org/proceedings/2007/120
ER  -