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  • 1
    Online Resource
    Online Resource
    Knowledge graphs and big data processing (2020)
    Cham, Switzerland : Springer
    Details
    UID:
    b3kat_BV046835043
    Format: 1 Online-Ressource , Illustrationen, Diagramme, Karten
    ISBN: 9783030531997
    Series Statement: Lecture notes in computer science 12072
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53198-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53200-0
    Language: English
    Subjects: Computer Science
    RVK:
    SS 4800
    Keywords: Datenbankverwaltung ; Information Retrieval ; Informationsmanagement ; Künstliche Intelligenz ; Big Data ; Datenanalyse ; Wissensbasis ; Aufsatzsammlung
    DOI: 10.1007/978-3-030-53199-7
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Fulltext
    Fulltext
    EUV Frankfurt
    HTW Berlin
    FH Potsdam
    BTU Cottbus
  • 2
    Online Resource
    Online Resource
    Knowledge Graphs and Big Data Processing (2020)
    [Erscheinungsort nicht ermittelbar] : Springer Nature
    Details
    UID:
    gbv_1778469078
    Format: 1 Online-Ressource (209 p.)
    ISBN: 9783030531997
    Series Statement: Lecture Notes in Computer Science; Information Systems and Applications, incl. Internet/Web, and HCI
    Content: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required
    Note: English
    Language: English
    URL: kostenfrei
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Stabi Berlin
    UB Potsdam
  • 3
    Online Resource
    Online Resource
    Knowledge Graphs and Big Data Processing / (2020)
    Springer Nature | Cham :Springer International Publishing :
    Details
    UID:
    almahu_9948574965702882
    Format: 1 online resource (XI, 209 p. 39 illus., 32 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 3-030-53199-6
    Series Statement: Information Systems and Applications, incl. Internet/Web, and HCI ; 12072
    Content: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
    Note: Foundations -- Chapter 1. Ecosystem of Big Data -- Chapter 2. Knowledge Graphs: The Layered Perspective -- Chapter 3. Big Data Outlook, Tools, and Architectures -- Architecture -- Chapter 4. Creation of Knowledge Graphs -- Chapter 5. Federated Query Processing -- Chapter 6. Reasoning in Knowledge Graphs: An Embeddings Spotlight -- Methods and Solutions -- Chapter 7. Scalable Knowledge Graph Processing using SANSA -- Chapter 8. Context-Based Entity Matching for Big Data -- Applications -- Chapter 9. Survey on Big Data Applications -- Chapter 10. Case Study from the Energy Domain. , English
    Additional Edition: ISBN 3-030-53198-8
    Language: English
    DOI: 10.1007/978-3-030-53199-7
    URL: https://doi.org/10.1007/978-3-030-53199-7
    URL: kostenfrei
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    HU Berlin
    UB Potsdam
  • 4
    Online Resource
    Online Resource
    Knowledge Graphs and Big Data Processing / (2020)
    Springer Nature | Cham :Springer International Publishing :
    Details
    UID:
    edoccha_9959633372902883
    Format: 1 online resource (XI, 209 p. 39 illus., 32 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 3-030-53199-6
    Series Statement: Information Systems and Applications, incl. Internet/Web, and HCI ; 12072
    Content: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
    Note: Foundations -- Chapter 1. Ecosystem of Big Data -- Chapter 2. Knowledge Graphs: The Layered Perspective -- Chapter 3. Big Data Outlook, Tools, and Architectures -- Architecture -- Chapter 4. Creation of Knowledge Graphs -- Chapter 5. Federated Query Processing -- Chapter 6. Reasoning in Knowledge Graphs: An Embeddings Spotlight -- Methods and Solutions -- Chapter 7. Scalable Knowledge Graph Processing using SANSA -- Chapter 8. Context-Based Entity Matching for Big Data -- Applications -- Chapter 9. Survey on Big Data Applications -- Chapter 10. Case Study from the Energy Domain. , English
    Additional Edition: ISBN 3-030-53198-8
    Language: English
    DOI: 10.1007/978-3-030-53199-7
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Charité
  • 5
    Online Resource
    Online Resource
    Knowledge Graphs and Big Data Processing / (2020)
    Springer Nature | Cham :Springer International Publishing :
    Details
    UID:
    edocfu_9959633372902883
    Format: 1 online resource (XI, 209 p. 39 illus., 32 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 3-030-53199-6
    Series Statement: Information Systems and Applications, incl. Internet/Web, and HCI ; 12072
    Content: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
    Note: Foundations -- Chapter 1. Ecosystem of Big Data -- Chapter 2. Knowledge Graphs: The Layered Perspective -- Chapter 3. Big Data Outlook, Tools, and Architectures -- Architecture -- Chapter 4. Creation of Knowledge Graphs -- Chapter 5. Federated Query Processing -- Chapter 6. Reasoning in Knowledge Graphs: An Embeddings Spotlight -- Methods and Solutions -- Chapter 7. Scalable Knowledge Graph Processing using SANSA -- Chapter 8. Context-Based Entity Matching for Big Data -- Applications -- Chapter 9. Survey on Big Data Applications -- Chapter 10. Case Study from the Energy Domain. , English
    Additional Edition: ISBN 3-030-53198-8
    Language: English
    DOI: 10.1007/978-3-030-53199-7
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    FU Berlin
  • 6
    Book
    Book
    Knowledge graphs and big data processing (2020)
    Cham : Springer
    Details
    UID:
    b3kat_BV046861215
    Format: xi, 209 Seiten , Illustrationen, Diagramme
    ISBN: 9783030531980
    Series Statement: Lecture notes in computer science 12072
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-030-53199-7
    Language: English
    Subjects: Computer Science
    RVK:
    SS 4800
    Keywords: Big Data ; Datenanalyse ; Wissensbasis ; Datenbankverwaltung ; Information Retrieval ; Informationsmanagement ; Künstliche Intelligenz ; Aufsatzsammlung ; Aufsatzsammlung
    Library Location Call Number Volume/Issue/Year Availability
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    Book
    TU Berlin get availability status
  • 7
    Online Resource
    Online Resource
    Knowledge graphs and big data processing / (2020)
    Cham, Switzerland :Springer,
    Details
    UID:
    edocfu_BV046835043
    Format: 1 Online-Ressource : , Illustrationen, Diagramme, Karten.
    ISBN: 978-3-030-53199-7
    Series Statement: Lecture notes in computer science 12072
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53198-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53200-0
    Language: English
    Subjects: Computer Science
    RVK:
    SS 4800
    Keywords: Datenbankverwaltung ; Information Retrieval ; Informationsmanagement ; Künstliche Intelligenz ; Big Data ; Datenanalyse ; Wissensbasis ; Aufsatzsammlung
    DOI: 10.1007/978-3-030-53199-7
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Fulltext
    Fulltext
    FU Berlin
  • 8
    Online Resource
    Online Resource
    Knowledge graphs and big data processing / (2020)
    Cham, Switzerland :Springer,
    Details
    UID:
    edoccha_BV046835043
    Format: 1 Online-Ressource : , Illustrationen, Diagramme, Karten.
    ISBN: 978-3-030-53199-7
    Series Statement: Lecture notes in computer science 12072
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53198-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53200-0
    Language: English
    Subjects: Computer Science
    RVK:
    SS 4800
    Keywords: Datenbankverwaltung ; Information Retrieval ; Informationsmanagement ; Künstliche Intelligenz ; Big Data ; Datenanalyse ; Wissensbasis ; Aufsatzsammlung
    DOI: 10.1007/978-3-030-53199-7
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Fulltext
    Fulltext
    Charité
  • 9
    Online Resource
    Online Resource
    Knowledge graphs and big data processing / (2020)
    Cham, Switzerland :Springer,
    Details
    UID:
    almafu_BV046835043
    Format: 1 Online-Ressource : , Illustrationen, Diagramme, Karten.
    ISBN: 978-3-030-53199-7
    Series Statement: Lecture notes in computer science 12072
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53198-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-53200-0
    Language: English
    Subjects: Computer Science
    RVK:
    SS 4800
    Keywords: Datenbankverwaltung ; Information Retrieval ; Informationsmanagement ; Künstliche Intelligenz ; Big Data ; Datenanalyse ; Wissensbasis ; Aufsatzsammlung
    DOI: 10.1007/978-3-030-53199-7
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Fulltext
    Fulltext
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