Advances in Case-Based Reasoning: 9th European Conference, by Isabelle Bichindaritz (auth.), Klaus-Dieter Althoff, Ralph

By Isabelle Bichindaritz (auth.), Klaus-Dieter Althoff, Ralph Bergmann, Mirjam Minor, Alexandre Hanft (eds.)

This ebook constitutes the refereed complaints of the ninth ecu convention on Case-Based Reasoning, ECCBR 2008, held in Trier, Germany, in September 2008.

The 34 revised examine papers and five revised program papers awarded including three invited talks have been rigorously reviewed and chosen from seventy one submissions. All present concerns in case-based reasoning are addressed, starting from theoretical and methodological matters to complicated purposes in numerous fields resembling wisdom discovery, similarity, context-awareness, uncertainty, and future health sciences.

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Extra resources for Advances in Case-Based Reasoning: 9th European Conference, ECCBR 2008, Trier, Germany, September 1-4, 2008. Proceedings

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Springer, Heidelberg (1999) 44. : Fish and shrink. a next step towards efficient case retrieval in large scaled case bases. Advances in Case-Based Reasoning, 362–376 (1996) 45. : Applying case retrieval nets to diagnostic tasks in technical domains. Advances in Case-Based Reasoning, 219–233 (1996) 46. : Exploiting background knowledge when learning similarity measures. Advances in Case-Based Reasoning, 169–183 (2004) 47. : Using evolution programs to learn local similarity measures. Case-Based Reasoning Research and Development, 1064 (2003) 48.

K. ) ICCBR 1999. LNCS (LNAI), vol. 1650, p. 719. Springer, Heidelberg (1999) 44. : Fish and shrink. a next step towards efficient case retrieval in large scaled case bases. Advances in Case-Based Reasoning, 362–376 (1996) 45. : Applying case retrieval nets to diagnostic tasks in technical domains. Advances in Case-Based Reasoning, 219–233 (1996) 46. : Exploiting background knowledge when learning similarity measures. Advances in Case-Based Reasoning, 169–183 (2004) 47. : Using evolution programs to learn local similarity measures.

Ie Abstract. After fifteen years of CBR conferences, this paper sets out to examine the themes that have evolved in CBR research as revealed by the implicit and explicit relationships between the conference papers. We have examined a number of metrics for demonstrating connections between papers and between authors and have found that a clustering based on co-citation of papers appears to produce the most meaningful organisation. We have employed an Ensemble Non-negative Matrix Factorisation (NMF) approach that produces a “soft” hierarchical clustering, where papers can belong to more than one cluster.

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