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Titlebook: Scalable Uncertainty Management; 7th International Co Weiru Liu,V. S. Subrahmanian,Jef Wijsen Conference proceedings 2013 Springer-Verlag B

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发表于 2025-3-21 19:48:23 | 显示全部楼层 |阅读模式
书目名称Scalable Uncertainty Management
副标题7th International Co
编辑Weiru Liu,V. S. Subrahmanian,Jef Wijsen
视频video
概述Fast-track conference proceeding of SUM 2013
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Scalable Uncertainty Management; 7th International Co Weiru Liu,V. S. Subrahmanian,Jef Wijsen Conference proceedings 2013 Springer-Verlag B
描述This book constitutes the refereed proceedings of the 7th International Conference on Scalable Uncertainty Management, SUM 2013, held in Washington, DC, USA, in September 2013. The 26 revised full papers and 3 revised short papers were carefully reviewed and selected from 57 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
出版日期Conference proceedings 2013
关键词conditional logic; event reasoning; knowledge representation; ontology; social network
版次1
doihttps://doi.org/10.1007/978-3-642-40381-1
isbn_softcover978-3-642-40380-4
isbn_ebook978-3-642-40381-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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Efficiently Estimating the Probability of Extensions in Abstract Argumentationvise a new Monte-Carlo simulation approach which is able to estimate ..(.) using much fewer samples than the state-of-the-art approach, resulting in a significantly more efficient estimation technique.
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Sound Source Localization from Uncertain Information Using the Evidential EM Algorithmes may be transposed to the data using belief functions. Then, we detail how the localization problem may be studied using a variant of the EM algorithm, known as Evidential EM algorithm. Eventually, we present simulation experiments which illustrate the advantage of using the Evidential EM algorithm when uncertain data are available.
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Enforcement in Argumentation Is a Kind of UpdateThis is done under some constraints about the allowed changes. We give a set of postulates restraining the class of enforcement operators and provide a representation theorem linking them to a family of proximity relations on argumentation systems.
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On the Implementation of a Multiple Output Algorithm for Defeasible Argumentationmputing each output and we provide an experimental evaluation of the algorithm based on two SAT encodings defined for the two main combinatorial subproblems that arise when computing warranted and blocked conclusions for each output.
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AFs with Necessities: Further Semantics and Labelling Characterizationgiven for Dung AFs and represent proper generalizations of them (in absence of the necessity relation, the classical semantics are recovered). Then, we show how to generalize Caminada’s labelling algorithms in presence of a necessity relation to compute the extensions under the studied semantics for AFNs.
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An Improvement of Subject Reacquisition by Reasoning and Revisionn interested zones such as airport security corridors. Also, to improve accuracy of reacquisition, we introduce the idea of revision as a method of post-processing. We demonstrate the significance and usefulness of our framework with an experiment which shows much less computational effort and better accuracy.
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PossDB: An Uncertainty Database Management Systemgnificant efforts by the database research community to develop new systems able to deal with uncertainty, either by annotating values with probabilistic measures or defining new structures capable of capturing missing information (e.g. Trio [3] and MayBMS [2]).
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