Elements of information theory
Elements of information theory
Knowledge intensive exception spaces
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Machine Learning and Data Mining; Methods and Applications
Machine Learning and Data Mining; Methods and Applications
Using k-d Trees to Improve the Retrieval Step in Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Case Memory and Retrieval Based on the Immune System
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Integration of Case Based Retrieval with a Relational Database System in Aircraft Technical Support
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
The Adaption Knowledge Bottleneck: How to Ease it by Learning from Cases
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Discovering Case Knowledge Using Data Mining
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Towards Dynamic Maintenance of Retrieval Knowledge in CBR
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Learning Adaptation Rules from a Case-Base
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
A study of instance-based algorithms for supervised learning tasks: mathematical, empirical, and psychological evaluations
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Acquiring case adaptation knowledge: a hybrid approach
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Using Case Provenance to Propagate Feedback to Cases and Adaptations
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Integrating Case-Based Reasoning and Meta-Learning for a Self-Improving Intelligent Tutoring System
International Journal of Artificial Intelligence in Education
Four Heads Are Better than One: Combining Suggestions for Case Adaptation
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Integrated introspective case-based reasoning for intelligent tutoring systems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Hi-index | 0.00 |
Adaptation is the least well studied process in case-based reasoning (CBR). The main reasons for this are the potentially complex nature of implementing adaptation knowledge and the difficulties associated with acquiring quality knowledge in the first place and competently maintaining it over time. For these reasons most CBR systems are designed to leave the adaptation component to the expert and therefore function simply as case retrieval systems as opposed to truly reasoning systems. Here we present a competent adaptation strategy, which uses a modified regression algorithm to automatically discover and implement locally specific adaptation knowledge in CBR. The advantages of this approach are that the adaptation knowledge acquisition process is automated, localised, guaranteed to be specific to the task at hand, and there is no adaptation knowledge maintenance burden on the system. The disadvantage is that the time taken to form solutions is increased but we also show how a novel indexing scheme based on k-means clustering can help reduce this overhead considerably.