Papadakis George (15 results)

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  • Condition: New

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    Condition: New. Idioma/Language: Español. *** Nota: Los envíos a España peninsular, Baleares y Canarias se realizan a través de mensajería urgente. No aceptamos pedidos con destino a Ceuta y Melilla.

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    SOFTCOVER. Condition: Fine. 1st Edition. Large 4to. in colour printed stiff glossy card covers, 96pp, colour plates, etc. Published to coincide with the exhibition 'Pop Art Show' at the Royal Academy of Arts, London . [CONDITION: A well preserved FINE very clean and tight unmarked copy in not far from new condition ] . . . We always ship in STRONG PROTECTIVE CARD PARCELS.

  • Language: English

    Published by Springer, 2021

    3031007506 / 9783031007507

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  • Language: English

    Published by Springer, 2021

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2021

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    Condition: New. 1st edition NO-PA16APR2015-KAP.

  • Language: English

    Published by Springer, 2021

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  • Language: English

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  • Language: English

    Published by Springer, 2021

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    Taschenbuch. Condition: Neu. The Four Generations of Entity Resolution | George Papadakis (u. a.) | Taschenbuch | Synthesis Lectures on Data Management | xvii | Englisch | 2021 | Springer | EAN 9783031007507 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by MORGAN & CLAYPOOL, 2021

    1636390560 / 9781636390567

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    Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

  • Language: English

    Published by Springer, 2021

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    Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand

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    Condition: new. Questo è un articolo print on demand.

  • Language: English

    Published by Springer, 2021

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  • Language: English

    Published by Springer International Publishing Mrz 2021, 2021

    3031007506 / 9783031007507

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency. The initial ER methods primarily target Veracity in the context of structured (relational) data that are described by a schema of well-known quality and meaning. To achieve high effectiveness, they leverage schema, expert, and/or external knowledge. Part of these methods are extended to address Volume, processing large datasets through multi-core or massive parallelization approaches, such as the MapReduce paradigm. However, these early schema-based approaches are inapplicable to Web Data, which abound in voluminous, noisy, semi-structured, and highly heterogeneous information. To address the additional challenge of Variety, recent works on ER adopt a novel, loosely schema-aware functionality that emphasizes scalability and robustness to noise. Another line of present research focuses on the additional challenge ofVelocity, aiming to process data collections of a continuously increasing volume. The latest works, though, take advantage of the significant breakthroughs in Deep Learning and Crowdsourcing, incorporating external knowledge to enhance the existing words to a significant extent. This synthesis lecture organizes ER methods into four generations based on the challenges posed by these four Vs. For each generation, we outline the corresponding ER workflow, discuss the state-of-the-art methods per workflow step, and present current research directions. The discussion of these methods takes into account a historical perspective, explaining the evolution of the methods over time along with their similarities and differences. The lecture also discusses the available ER tools and benchmark datasets that allow expert as well as novice users to make use of the available solutions. 172 pp. Englisch.

  • Language: English

    Published by Springer, 2021

    3031007506 / 9783031007507

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  • Language: English

    Published by Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2021

    3031007506 / 9783031007507

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency. The initial ER methods primarily target Veracity in the context of structured (rela.

  • Language: English

    Published by Springer, Springer Mär 2021, 2021

    3031007506 / 9783031007507

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency. The initial ER methods primarily target Veracity in the context of structured (relational) data that are described by a schema of well-known quality and meaning. To achieve high effectiveness, they leverage schema, expert, and/or external knowledge. Part of these methods are extended to address Volume, processing large datasets through multi-core or massive parallelization approaches, such as the MapReduce paradigm. However, these early schema-based approaches are inapplicable to Web Data, which abound in voluminous, noisy, semi-structured, and highly heterogeneous information. To address the additional challenge of Variety, recent works on ER adopt a novel, loosely schema-aware functionality that emphasizes scalability and robustness to noise. Another line of present research focuses on the additional challenge ofVelocity, aiming to process data collections of a continuously increasing volume. The latest works, though, take advantage of the significant breakthroughs in Deep Learning and Crowdsourcing, incorporating external knowledge to enhance the existing words to a significant extent. This synthesis lecture organizes ER methods into four generations based on the challenges posed by these four Vs. For each generation, we outline the corresponding ER workflow, discuss the state-of-the-art methods per workflow step, and present current research directions. The discussion of these methods takes into account a historical perspective, explaining the evolution of the methods over time along with their similarities and differences. The lecture also discusses the available ER tools and benchmark datasets that allow expert as well as novice users to make use of the available solutions.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.