Titlebook: Scalable Uncertainty Management; 6th International Co Eyke Hüllermeier,Sebastian Link,Bernhard Seeger Conference proceedings 2012 Springer-

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书目名称Scalable Uncertainty Management影响因子(影响力)




书目名称Scalable Uncertainty Management影响因子(影响力)学科排名




书目名称Scalable Uncertainty Management网络公开度




书目名称Scalable Uncertainty Management网络公开度学科排名




书目名称Scalable Uncertainty Management被引频次




书目名称Scalable Uncertainty Management被引频次学科排名




书目名称Scalable Uncertainty Management年度引用




书目名称Scalable Uncertainty Management年度引用学科排名




书目名称Scalable Uncertainty Management读者反馈




书目名称Scalable Uncertainty Management读者反馈学科排名

花争吵

Generalizing Naive and Stable Semantics in Argumentation Frameworks with Necessities and Preferencesith necessities. We propose a full characterization of stable and naive semantics in this new context by new sets of adapted postulates and we present a practical method to compute them by using a classical Dung argumentation framework.

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产生

Xtream: A System for Continuous Querying over Uncertain Data Streamsanagement systems and object monitoring systems which need both issues in tandem. The existence of complex correlations and lineages prevents Probabilistic DBMSs (PDBMSs) from continuously querying temporal positioning and sensed data. Our main contribution is developing a new system to continuously

智力高

Managing Uncertainty in Databases and Scaling It Up to Concurrent Transactionshe usual requirement that integrity constraints must always be satisfied needs to be renounced for constraints that model uncertainty. That is possible due to the recently introduced inconsistency tolerance of methods for integrity checking, integrity repair and query answering. Inconsistency tolera

BUMP

Generalizing Naive and Stable Semantics in Argumentation Frameworks with Necessities and Preferencess of a relation encoding this semantics and defined on subsets of arguments. Furthermore, a set of postulates is proposed to provide a full characterization of any relation encoding the generalized stable semantics. In this paper, we adapt this approach to preference-based argumentation frameworks w

Palpate

Stable Semantics in Logic-Based Argumentationem may have. We show that in the best case, an argumentation system infers exactly the common conclusions drawn from the maximal consistent subbases of the original knowledge base. This output corresponds to that returned by a system under the naive semantics. In the worst case, counter-intuitive re

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