Provenance data science models (15 resultados)
Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 139,30
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Condición: New. In.
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 136,77
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Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 156,36
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Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 209,53
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Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 140,10
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Taschenbuch. Condición: Neu. Provenance in Data Science | From Data Models to Context-Aware Knowledge Graphs | Leslie F. Sikos (u. a.) | Taschenbuch | Advanced Information and Knowledge Processing | xi | Englisch | 2022 | Springer | EAN 9783030676834 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 6…9121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 162,91
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-ba…sed representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
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EUR 122,67
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Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, kno…wledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Idioma: Inglés
Editorial: Palgrave Macmillan, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
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EUR 118,72
Envío por EUR 105,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, kno…wledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
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Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 167,14
Envío por EUR 61,01Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge g…raph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs
Sikos, Leslie F. (Edited by)/ Seneviratne, Oshani W. (Edited by)/ McGuinness, Deborah L. (Edited by)
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 233,75
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Hardcover. Condición: Brand New. 121 pages. 9.25x6.10x0.51 inches. In Stock.
Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 220,06
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Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 224,47
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Condición: New. PRINT ON DEMAND.
