Mining high-speed data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Learning When to Collaborate among Learning Agents
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Collaborative Case-Based Reasoning: Applications in Personalised Route Planning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Ensemble Case-Based Reasoning: Collaboration Policies for Multiagent Cooperative CBR
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
When Two Case Bases Are Better than One: Exploiting Multiple Case Bases
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Managing Multiple Case Bases: Dimensions and Issues
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Learning and joint deliberation through argumentation in multiagent systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Knowledge Planning and Learned Personalization for Web-Based Case Adaptation
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Horizontal Case Representation
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
An argumentation-based framework for deliberation in multi-agent systems
ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
Language games: solving the vocabulary problem in multi-case-base reasoning
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Extending CBR with multiple knowledge sources from web
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Recommending case bases: applications in social web search
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
eXiT*CBR.v2: Distributed case-based reasoning tool for medical prognosis
Decision Support Systems
Multiagent and Grid Systems
| Hi-index | 0.00 |
Case-based reasoning (CBR) systems solve new problems by retrieving stored prior cases, and adapting their solutions to fit new circumstances. Traditionally, CBR systems draw their cases from a single local case-base tailored to their task. However, when a system's own set of cases is limited, it may be beneficial to supplement the local case-base with cases drawn from external casebases for related tasks. Effective use of external case-bases requires strategies for multi-case-base reasoning (MCBR): (1) for deciding when to dispatch problems to an external case-base, and (2) for performing cross-case-base adaptation to compensate for differences in the tasks and environments that each case-base reflects. This paper presents methods for automatically tuning MCBR systems by selecting effective dispatching criteria and cross-case-base adaptation strategies. The methods require no advance knowledge of the task and domain: they perform tests on an initial set of problems and use the results to select strategies reflecting the characteristics of the local and external case-bases. We present experimental illustrations of the performance of the tuning methods for a numerical prediction task, and demonstrate that a small sample set can be sufficient to make high-quality choices of dispatching and cross-case-base adaptation strategies.