Probabilistic Databases by Suciu Dan (18 results)

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  • Language: English

    Published by Springer, 2011

    3031007514 / 9783031007514

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  • Language: English

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  • Language: English

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  • Language: English

    Published by Springer, 2011

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  • Language: English

    Published by Springer, 2011

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    Condition: New. pp. 164.

  • Language: English

    Published by Springer 2011-06, 2011

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  • Language: English

    Published by Springer, 2011

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  • Language: English

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  • Language: English

    Published by Morgan & Claypool Publishers, 2011

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    paperback. Condition: Gut. 180 Seiten; 9781608456802.3 Gewicht in Gramm: 500.

  • Language: English

    Published by Now Publishers, 2017

    1680833146 / 9781680833140

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    Language: English

    Published by Springer, 2011

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    Taschenbuch. Condition: Neu. Probabilistic Databases | Dan Suciu (u. a.) | Taschenbuch | Synthesis Lectures on Data Management | xv | Englisch | 2011 | Springer | EAN 9783031007514 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

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  • Language: English

    Published by Springer, 2011

    3031007514 / 9783031007514

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  • Language: English

    Published by Springer, 2011

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    Condition: New. Print on Demand pp. 164 This item is printed on demand.

  • Language: English

    Published by Springer, 2011

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    Condition: New. PRINT ON DEMAND pp. 164.

  • Language: English

    Published by Springer International Publishing Jun 2011, 2011

    3031007514 / 9783031007514

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced Techniques 184 pp. Englisch.

  • Language: English

    Published by Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2011

    3031007514 / 9783031007514

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data.

  • Language: English

    Published by Springer, Palgrave Macmillan Jun 2011, 2011

    3031007514 / 9783031007514

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced TechniquesSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.