Case-based reasoning
Adaptation-guided retrieval: questioning the similarity assumption in reasoning
Artificial Intelligence
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
The Utility Problem Analysed: A Case-Based Reasoning Perspective
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Using knowledge to isolate search in route finding
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Stratified case-based reasoning: reusing hierarchical problem solving episodes
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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
An Accurate Adaptation-Guided Similarity Metric for Case-Based Planning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Discovering personalized routes from trajectories
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Leveraging the contributory potential of user feedback
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Automatically generating high-quality routes using real map data is difficult for a number of reasons. Real maps rarely contain the sort of information that is useful for constructing high quality routes. In addition, the notion of "route quality" is difficult to define and is likely to change from person to person. In this sense the automatic construction of high-quality routes that match the preferences of individuals is an example of a weak-theory problem, and therefore well suited to a case-based approach. In this paper we describe and evaluate a case-based route planning system that is capable of efficiently generating routes that reflect the implicit preferences of individual users.