Learning similarity measures: A formal view based on a generalized CBR model

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 3620, Issue , 2005, Pages 507-521

  Stahl, Armin ^a  

^a GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; SYSTEMS ANALYSIS;

CASE BASED REASONING (CBR); GOAL-DIRECTED CHOICE; LEARNING TECHNIQUES;

LEARNING SYSTEMS;

EID: 26944445813     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11536406_39     Document Type: Conference Paper

References (21)

1. Proceedings of the ECCBR-2004 Workshop on Explanation, 2004.
2. Aamodt, A., Plaza, E. Case-based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications, 7(1):39-59, 1994.
3. Bergmann, R., Richter, M.M., Schmitt, S., Stahl, A., Vollrath, I. Utility-Oriented Matching: A New Research Direction for Case-Based Reasoning. In Proceedings of the 1st Conference on Professional Knowledge Management. Shaker, 2001.
4. Blanzieri, E., Ricci, F. Probability Based Metrics for Nearest Neighbor Classification and Case-Based Reasoning. In Proceedings of the 3rd International Conference on Case-Based Reasoning. Springer, 1999.
5. Bonzano, A., Cunningham, P., Smyth, B. Using Introspective Learning to Improve Retrieval in CBR: A Case Study in Air Traffic Control. In Proceedings of the 2nd International Conference on Case-Based Reasoning. Springer, 1997.
6. Branting, K. Acquiring Customer Preferences from Return-Set Selections. In Proceedings of the 4th International Conference on CBR. Springer, 2001.
7. Breuel, T. Character Recognition by Adaptive Statistical Similarity. In Proceedings of the 7th Int. Conf. on Document Analysis and Recognition. Springer, 2003.
8. Burke, R. The Wasabi Personal Shopper: A Case-Based Recommender System. In Proceedings of the 11th International Conference on Innovative Applications of Artificial Intelligence, 1999.
9. Coyle, L., Cunningham, P. Exploiting Re-ranking Information in a Case-Based Personal Travel Assistent. In Workshop on Mixed-Initiative Case-Based Reasoning at the 5th International Conference on Case-Based Reasoning. Springer, 2003.
10. Gabel, T. On the Use of Vocabulary Knowledge for Learning Similarity Measures. In Proceedings of the 3rd German Workshop on Experience Management. Springer, 2005.
11. Gabel, T., Stahl, A. Exploiting Background Knowledge when Learning Similarity Measures. In Proceedings of the 7th European Conference on Case-Based Reasoning. Springer, 2004.
12. Lowe, D. Similarity Metric Learning for a Variable-Kernel Classifier. Neural Computation, 7, 1993.
13. Richter, M. M. The Knowledge Contained in Similarity Measures. Invited Talk at ICCBR'95, 1995.
14. Schmitt, S. Dialog Tailoring for Similarity-Based Electronic Commerce Systems. dissertation.de, 2003.
15. Stahl, A. Learning Feature Weights from Case Order Feedback. In Proceedings of the 4th International Conference on Case-Based Reasoning. Springer, 2001.
16. Stahl, A. Learning of Knowledge-Intensive Similarity Measures in Case-Based Reasoning, volume 986. dissertation.de, 2004.
17. Stahl, A., Gabel, T. Using Evolution Programs to Learn Local Similarity Measures. In Proceedings of the 5th International Conference on CBR. Springer, 2003.
18. Stahl, A., Schmitt, S. Optimizing Retrieval in CBR by Introducing Solution Similarity. In Proceedings of the Int. Conf. on AI. CSREA Press, 2002.
19. Wettschereck, D., Aha, D. W. Weighting Features. In Proceeding of the 1st International Conference on Case-Based Reasoning. Springer, 1995.
20. Wilke, W., Bergmann, R. Considering Decision Cost During Learning of Feature Weights. In Proceedings of the 3rd European Workshop on CBR. Springer, 1996.
21. Zhang, Z., Yang, Q. Dynamic Refinement of Feature Weights Using Quantitative Introspective Learning. In Proceedings of the 16th International Joint Conference on Artificial Intelligence, 1999.