9783030676834 - provenance in data science: from data models to context-aware knowledge graphs (12 risultati)
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: Buchpark, Trebbin, GermaniaBuchpark
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Condizione: 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, 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.
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Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: 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-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.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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Softcover. Condizione: gut. 2022. Provenance in Data Science In deutscher Sprache. pages.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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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, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
- Brossura
- Print on Demand
Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Condizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
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Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland Apr 2022, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: 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-a…ware, knowledge 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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Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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-enhance…d, provenance-aware, knowledge graph-base.
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Lingua: Inglese
Editore: Springer, Springer Apr 2022, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: 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 Commu…nication 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.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2022
Serie: Libro 65 di 66 - Advanced Information and Knowledge Processing
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
