A case-based reasoning framework for workflow model management
Data & Knowledge Engineering - Special issue: Advances in business process management
Automated case base creation and management
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Automated case creation and management for diagnostic CBR systems
Applied Intelligence
A CBR-Based Approach for Ship Collision Avoidance
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Case-based ranking for decision support systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
The design of a fuzzy-neural network for ship collision avoidance
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
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With the rapid development of case-based reasoning (CBR) techniques, CBR has been widely applied to real-world applications such as agent-based systems for ship collision avoidance. A successful CBR-based system relies on a high-quality case base. Automated case creation technique is highly demanded. In this paper, we propose an automated case learning method for CBR-based agent systems. Building on techniques from CBR and natural language processing, we developed a method for learning cases from maritime affair records. After reviewing the developed agent-based systems for ship collision avoidance, we present the proposed framework and the experiments conducted in case generation. The experimental results show the usefulness and applicability of case learning approach for generating cases from the historic maritime affair records.