Titlebook: Case-Based Reasoning Research and Development; 22nd International C Luc Lamontagne,Enric Plaza Conference proceedings 2014 Springer Interna

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Planning of Radiation Treatment,system in the course of time. More specifically, our method makes use of an underlying probabilistic model and realizes adaptation as Bayesian inference. The effectiveness of this method is illustrated in a case study that deals with the case-based recommendation of red wines.

大约冬季

Present Trends in Luminescence Research,ing revision operators and algorithms in DLs can not be used for this formalism. Finally we present our adaptation algorithm. Our algorithm is syntax-independent and fine-grained, and satisfies the requirements on revision operators.

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Absorption and Emission Spectra, use ANN for improved adaptation and similarity determination. The approaches are evaluated in several configurations using a training set of 4,231 actual domain transactions, which demonstrates their high usefulness.

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Algorithm for Adapting Cases Represented in a Tractable Description Logicing revision operators and algorithms in DLs can not be used for this formalism. Finally we present our adaptation algorithm. Our algorithm is syntax-independent and fine-grained, and satisfies the requirements on revision operators.

MOCK

A Hybrid CBR-ANN Approach to the Appraisal of Internet Domain Names use ANN for improved adaptation and similarity determination. The approaches are evaluated in several configurations using a training set of 4,231 actual domain transactions, which demonstrates their high usefulness.

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0302-9743 2014) held in Cork, Ireland, in September 2014. The 35 revised full papers presented were carefully reviewed and selected from 49 submissions. The presentations cover a wide range of CBR topics of interest both to researchers and practitioners including case retrieval and adaptation, similarity asse

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https://doi.org/10.1007/978-1-4684-3291-6e spanned by instances along the decision boundary. Experiments over collections of varying complexity show that the measure exhibits strong negative correlation with classification accuracies over several classifiers. We also present empirical findings from experiments over non-textual datasets.

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