9783030676803 - provenance in data science: from data models to context-aware knowledge graphs (advanced information and knowledge processing) (14 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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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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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 156,61
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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: 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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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.
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 234,12
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Hardcover. Condición: Brand New. 121 pages. 9.25x6.10x0.51 inches. In Stock.
Idioma: Inglés
Editorial: Palgrave Macmillan, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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Hardcover. Condición: gut. 2021. Provenance in Data Science In deutscher Sprache. pages.
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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Condición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
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Idioma: Inglés
Editorial: Springer International Publishing, Springer Nature Switzerland Apr 2021, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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, kn…owledge 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. 124 pp. Englisch.
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Idioma: Inglés
Editorial: Springer International Publishing, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: moluna, Greven, Alemaniamoluna
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EUR 136,16
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations to be used for information processing, management, aggregation,…fusion, and visualization.
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Idioma: Inglés
Editorial: Springer, Springer Apr 2021, 2021
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 160,49
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Evolution of Context-Aware RDF Knowledge Graphs.- Data Provenance and Accountability on the Web.- The Right (Provenance) Hammer for the Job: a Comparison of Data Provenance Instrumentation.- Contextualized Knowledge Graphs in Communication… Network and Cyber-Physical System Modeling.- ProvCaRe: A Large-Scale Semantic Provenance Resource for Scientific Reproducibility.- Graph-Based Natural Language Processing for the Pharmaceutical Industry.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 124 pp. Englisch.
