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Advances in Probabilistic Databases for Uncertain Information Management [electronic resource] / edited by Zongmin Ma, Li Yan.

By: Ma, Zongmin [editor.].
Contributor(s): Yan, Li [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Fuzziness and Soft Computing: 304Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: X, 161 p. 23 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642375095.Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics) | Information Systems Applications (incl. Internet)DDC classification: 519 Online resources: Click here to access online
Contents:
1   Research in Probabilistic Spatiotemporal Databases: The SPOT Framework -- 2   A Probabilistic Object-Oriented Database Model with Fuzzy Measures -- 3   Probabilistic XML: Models and Complexity -- 4   Uncertain Data: Representations, Query Processing, and Applications -- 5   A Theoretically-Sound Approach for OLAPing Uncertain and Imprecise Multidimensional Data Streams -- 6   Tractable Probabilistic Description Logic Programs.  .
In: Springer eBooksSummary: This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
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1   Research in Probabilistic Spatiotemporal Databases: The SPOT Framework -- 2   A Probabilistic Object-Oriented Database Model with Fuzzy Measures -- 3   Probabilistic XML: Models and Complexity -- 4   Uncertain Data: Representations, Query Processing, and Applications -- 5   A Theoretically-Sound Approach for OLAPing Uncertain and Imprecise Multidimensional Data Streams -- 6   Tractable Probabilistic Description Logic Programs.  .

This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.

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