New PDF release: Advances in Case-Based Reasoning: 8th European Conference,

By Edwina L. Rissland (auth.), Thomas R. Roth-Berghofer, Mehmet H. Göker, H. Altay Güvenir (eds.)

ISBN-10: 3540368434

ISBN-13: 9783540368434

This booklet constitutes the refereed lawsuits of the eighth eu convention on Case-Based Reasoning, ECCBR 2004, held in Fethiye, Turkey in September 2006.

The 31 revised complete papers and five revised program papers offered including 2 invited papers and a pair of abstracts of invited talks have been rigorously reviewed and chosen from quite a few submissions. All present matters in case-based reasoning, starting from theoretical and methodological matters to complicated functions in quite a few fields are addressed, hence featuring a consultant photo of present CBR research.

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Additional resources for Advances in Case-Based Reasoning: 8th European Conference, ECCBR 2006 Fethiye, Turkey, September 4-7, 2006 Proceedings

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Proceedings of the 13th European Conference on Artificial Intelligence. Wiley, Chichester (1998) 68-72 43. : Case-base Maintenance by Integrating Case-Index Revision and CaseRetention Policies in a Derivational Replay Framework. Computational Intelligence 17 (2001) 280-294 44. : Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, New Jersey (1995) Is Consideration of Background Knowledge in Data Driven Solutions Possible at All? com Abstract. In Data Driven Solutions using CBR or Data Mining approaches the optimal results can be achieved if one can consider and use, besides available data and texts, all other available information sources like general and background knowledge.

Another important feature that CDR shares with k-NN is that an otherwise competitive case can often compensate for its failure to satisfy one or more of the constraints satisfied by another case. As shown in Completeness Criteria for Retrieval in Recommender Systems 21 Fig. 2, the CDR retrieval set for our example case base and query in the property domain is {Case 1, Case 3, Case 5}. Although Case 3 (Y N N N) fails to satisfy one of the constraints satisfied by Case 5 (Y N Y N), the greater similarity of Case 3 ensures that it is not excluded from the CDR retrieval set.

One important benefit is that recommendations based on incomplete queries can be justified on the basis that any user preferences that remain unknown cannot affect the recommendation. However, like any retrieval strategy in which only a single case (or set of equally similar cases) is recommended, and no attempt is made to identify constraints that must be satisfied, iNN is incomplete. In any recommender system, of course, more than a single recommendation cycle may be needed to retrieve a case that is acceptable to the user.

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Advances in Case-Based Reasoning: 8th European Conference, ECCBR 2006 Fethiye, Turkey, September 4-7, 2006 Proceedings by Edwina L. Rissland (auth.), Thomas R. Roth-Berghofer, Mehmet H. Göker, H. Altay Güvenir (eds.)


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