A knowledge-intensive, integrated approach to problem solving and sustained learning
A knowledge-intensive, integrated approach to problem solving and sustained learning
Retrieving Adaptable Cases: The Role of Adaptation Knowledge in Case Retrieval
EWCBR '93 Selected papers from the First European Workshop on Topics 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
Applying Recursive CBR for the Custumization of Structured Products in an Electronic Shop
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Similarity Assessment for Generalizied Cases by Optimization Methods
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
Towards a Unified Theory of Adaption in Case-Based Reasoning
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
Generalized Cases: Representation and Steps Towards Efficient Similarity Assessment
KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Adaptation Using Constraint Satisfaction Techniques
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Retrieval and configuration of life insurance policies
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Optimization Algorithms to Find Most Similar Deductive Consequences (MSDC)
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
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While reasoning with cases is usually done in a similarity-based manner, additional general knowledge is often represented in rules, constraints, or ontology definitions and is applied in a deductive reasoning process. This paper presents a new view on the combination of deductive and similarity-based reasoning, which is embedded in the CBR context. The basic idea is to view general knowledge and cases as a logical theory of a domain. Similarity-based reasoning is introduced as search for the most similar element in the deductive closure of the domain theory. We elaborate this approach and introduce several related search algorithms, which are analyzed in an experimental study. Further, we show how several previous approaches for using general knowledge in CBR can be mapped to our new view.