Titlebook: Belief Functions: Theory and Applications; 5th International Co Sébastien Destercke,Thierry Denoeux,Arnaud Martin Conference proceedings 20

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Formal Methods Through Domain Engineering,operty that characterizes Shannon’s definitions of entropy and conditional entropy for discrete probability distributions. None of the existing definitions of entropy for belief functions in the D-S theory satisfy such a compound distributions property. We describe some important properties of our definition.

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Vicki V. Vandaveer,Tracey E. RizzutoWe propose the use of Smets and PCR5 rules to merge artificial geophysical and geotechnical data, as part of fluvial levee assessment. It highlights the ability to characterize the presence of interfaces and a geological anomaly.

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An Evidential Collaborative Filtering Approach Based on Items Contents Clustering,king process. Among the various recommendation approaches, Collaborative Filtering (CF) is considered as one of the most popular techniques in RSs. CF techniques are categorized into model-based and memory-based. Model-based approaches consist in learning a model from past ratings to perform predict

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The Belief Functions Theory for Sensors Localization in Indoor Wireless Networks,zation where the objective is to determine the zone where the mobile sensor resides at any instant. The proposed approach uses the belief functions theory to define an evidence framework, for estimating the most probable sensor’s zone. Real experiments demonstrate the effectiveness of this approach

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On Evidential Clustering with Partial Supervision, a credal partition coherent with the background knowledge. The main characteristics of the new method is its ability to express the uncertainties of partial prior information by assigning each constrained object to a set of labels. It enriches previous existing algorithm that allows the preservatio

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Exploiting Domain-Experts Knowledge Within an Evidential Process for Case Base Maintenance,to improve their problem-solving performance and competence. However, to the best of our knowledge, all of them are not able to make use of prior knowledge which can be offered by domain experts, especially that CBR is widely applied in real-life domains. For instance, given symptoms of two differen

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