A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
CaBaTa: case-based reasoning for holiday planning
Proceedings of the international conference on Information and communications technologies in tourism
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Explanation-Driven Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Design of a Case-Based Reasoning System Applied to Neuropathy Diagnosis
EWCBR '94 Selected papers from the Second European Workshop on Advances 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
An Architecture for Knowledge Intensive CBR Systems
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Using Configuration Techniques for Adaptation
Case-Based Reasoning Technology, From Foundations to Applications
CBROnto: A Task/Method Ontology for CBR
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Components for Case-Based Reasoning Systems
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
The evolution of Protégé: an environment for knowledge-based systems development
International Journal of Human-Computer Studies
Building CBR systems with jcolibri
Science of Computer Programming
Rapid Prototyping of CBR Applications with the Open Source Tool myCBR
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Case-Based reasoning within semantic web technologies
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
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Case-Based Reasoning CBR is a powerful tool for decision making as it approaches human natural thinking process, based on the reuse of past experiences in solving new problems. A CBR system is a combination of processes and knowledge called "knowledge containers", its reasoning power can be improved through the use of domain knowledge. CBR systems combining case specific knowledge with general domain knowledge models are called Knowledge Intensive CBR KI-CBR. Although CBR claims to reduce the effort required for developing knowledge-based systems substantially when compared with more traditional Artificial Intelligence approaches, the implementation of a CBR application from scratch is still a time consuming task. The present work aims to develop a CBR application for fault diagnosis of steam turbines that integrates a domain knowledge modeling in an ontological form and focuses on the similarity-based retrieval step. This system is viewed as a KI-CBR system based on domain ontology, built around jCOLIBRI and myCBR, two well-known frameworks to design KI-CBR systems. During the prototyping process, the use and functionality of the two focused frameworks are examined. A comparative study is performed with results presenting advantages provided by the use of ontologies with CBR systems and demonstrating that jCOLIBRI is well adapted to design KI-CBR system.