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Titlebook: Scalable Uncertainty Management; Third International Lluís Godo,Andrea Pugliese Conference proceedings 2009 Springer-Verlag Berlin Heidelb

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书目名称Scalable Uncertainty Management
副标题Third International
编辑Lluís Godo,Andrea Pugliese
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Scalable Uncertainty Management; Third International  Lluís Godo,Andrea Pugliese Conference proceedings 2009 Springer-Verlag Berlin Heidelb
描述This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.
出版日期Conference proceedings 2009
关键词Argumentation; OWL ontologies; calculus; description logics; fuzzy logic; incomplete data; inconsistency; l
版次1
doihttps://doi.org/10.1007/978-3-642-04388-8
isbn_softcover978-3-642-04387-1
isbn_ebook978-3-642-04388-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2009
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A Model Based on Possibilistic Certainty Levels for Incomplete Databases, considered, and that ii) the data complexity associated with the extended operators in this context is the same as in the classical database case, which makes the approach highly scalable. A possibilistic logic encoding of the model is also outlined.
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Explaining Inconsistencies in OWL Ontologies,ications for inconsistent ontologies are more “difficult” to compute and are often more “numerous” than justifications for entailments in consistent ontologies: whereas it is always possible to compute . justifications, it is often not possible to compute . justifications for real world inconsistent ontologies.
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PrDB: Managing Large-Scale Correlated Probabilistic Databases (Abstract),l inference and probabilistic modeling often introduce another layer of uncertainty on top of that. Examples of such data include measurement data collected by sensor networks, observation data in the context of social networks, scientific and biomedical data, and data collected by various online cy
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Bridging the Gap between Abstract Argumentation Systems and Logic,o indication is given on how to instantiate this setting, i.e. how to build arguments from a . and how to choose an appropriate attack relation. This leads in some cases to undesirable results like inconsistent extensions (i.e. the set of formulas forming an extension is inconsistent). This is due t
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Interventions in Possibilistic Logic,in Bayesian net structures (or in their possibilistic counterpart) until now. The paper proposes an approach to the representation and the handling of intervention-like pieces of knowledge, in the setting of possibilistic logic. It is compatible with a modeling of the way agents perceive causal rela
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An Argument-Based Approach to Using Multiple Ontologies, logic-based argumentation is that an argument is a pair 〈.,.〉 where . is a minimal subset of the knowledgebase such that . is consistent and . entails the claim .. Using dialogue games, agents (each with its own ontology) can exchange arguments and counterarguments concerning formulae of interest.
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