A Logical Representation for Relevance Criteria
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Similarity Measures for Object-Oriented Case Representations
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Study and Formalization of a Case-Based Reasoning System Using a Description Logic
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
An Architecture for Knowledge Intensive CBR Systems
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Cases as terms: A feature term approach to the structured representation of cases
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Similarity Metrics: A Formal Unification of Cardinal and Non-Cardinal Similarity Measures
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Adaptation Using Iterated Estimations
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
A Value Supplementation Method for Case Bases with Incomplete Information
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Opportunities for CBR in learning by doing
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Retrieval over conceptual structures
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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This paper focuses on the design of knowledge intensive CBR systems and introduces a domain-independent architecture to help it. Our approach is based on acquiring the domain knowledge by reusing knowledge from a library of ontologies and integrating it with CBROnto, a task based ontology comprising common CBR terminology. In this paper we focus in retrieval and similarity assessment processes taking advantage of this domain knowledge. We describe our CBROnto based similarity representation framework and explain how it is used to represent similarity measures and retrieval processes.