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Titlebook: Scalable Uncertainty Management; 5th International Co Salem Benferhat,John Grant Conference proceedings 2011 Springer-Verlag GmbH Berlin He

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书目名称Scalable Uncertainty Management
副标题5th International Co
编辑Salem Benferhat,John Grant
视频video
概述State-of-the-art research.Fast-track conference proceedings.Unique visibility
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Scalable Uncertainty Management; 5th International Co Salem Benferhat,John Grant Conference proceedings 2011 Springer-Verlag GmbH Berlin He
描述This book constitutes the refereed proceedings of the 5th International Conference on Scalable Uncertainty Management, SUM 2011, held in Dayton, OH, USA, in October 2011. The 32 revised full papers and 3 revised short papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on argumentation systems, probabilistic inference, dynamic of beliefs, information retrieval and databases, ontologies, possibility theory and classification, logic programming, and applications.
出版日期Conference proceedings 2011
关键词credibility models; fuzzy logic; incomplete information; knowledge representation; risk management; uncer
版次1
doihttps://doi.org/10.1007/978-3-642-23963-2
isbn_softcover978-3-642-23962-5
isbn_ebook978-3-642-23963-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2011
The information of publication is updating

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Scalable Uncertainty Management978-3-642-23963-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Salem Benferhat,John GrantState-of-the-art research.Fast-track conference proceedings.Unique visibility
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Dynamics of Beliefs paper we give a quick overview of the main operators for belief change, in particular revision, update, and merging, when the beliefs are represented in propositional logic. And we discuss some works on belief change in more expressive frameworks.
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Fuzzy Classifiers – Opportunities and Challenges –o attribute/feature selection, adoption of a specific approach/algorithm, evaluate the classifier performance, etc. We consider the opportunities that such classifiers have to offer and contrast them with the challenges they pose.
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A Heuristics-Based Pruning Technique for Argumentation Treesg information in contradiction. Computation of warrant tends to be expensive; in order to alleviate this issue, we propose a heuristics-based pruning technique over dialectical trees. Empirical testing shows that in most cases our approach answers queries much faster than the usual techniques, which prune with no guide.
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