Isbn: 9783030924294 - relational calculus for actionable knowledge (15 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    3030924297 / 9783030924294

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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    Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, 'Knowledge Discovery and Data Mining' (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge.Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authorsprovide an understanding of the concept of 'relation' and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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

  • Lingua: Inglese

    Editore: Springer International Publishing Jan 2022, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, 'Knowledge Discovery and Data Mining' (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge.Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authorsprovide an understanding of the concept of 'relation' and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering. 360 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, Berlin|Springer International Publishing|Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity.This book focuse.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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  • Lingua: Inglese

    Editore: Springer, Springer Jan 2022, 2022

    3030924297 / 9783030924294

    Serie: Libro 9 di 9 - Information Fusion and Data Science

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, 'Knowledge Discovery and Data Mining' (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge.Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authors provide an understanding of the concept of 'relation' and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 360 pp. Englisch.