Titlebook: Scalable Uncertainty Management; Second International Sergio Greco,Thomas Lukasiewicz Conference proceedings 2008 Springer-Verlag Berlin He

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0302-9743 ate theoretical techniques required to manage the uncertainty that arises in large scale real world applications and to cope with large volumes of uncertainty and inconsistency in databases, the Web, the semantic Web, and artificial intelligence in general.978-3-540-87992-3978-3-540-87993-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Prabhakar RaghavanSteganografie .in modernen Netzwerken.Die Sicherheit des .Internets der Dinge. und sein Einsatz etwa in Smart Buildings und Industriesteueranlagen..Das Buch ist so konzipiert, dass Leserinnen und Leser mit eine978-3-658-33423-9

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Uncertainty Management for the Retrieval of Economic Information from Distributed Markets,yze the properties and the completeness of information in Grid markets. Therefore, we simulate Grid market specific scenarios under complete and incomplete information provision by varying the information accessibility. The results confirm the influence of the accuracy on the stability of the market

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Approximate Reasoning for Efficient Anytime Induction from Relational Knowledge Bases, that reformulates a multi-relational learning task into an attribute-value one. In this paper we propose an . technique that decreases the complexity of a relational problem changing both the language and the inference operation used for the deduction. The complexity of the FOL language is decrease

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Clustering Uncertain Data Via K-Medoids,signed to overcome the above issues. In particular, our UK-medoids algorithm employs distance functions properly defined for uncertain objects, and exploits a K-medoids scheme. Experiments have shown that UK-medoids outperforms existing algorithms from an accuracy viewpoint while achieving reasonabl