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020 _a9783030531997
_9978-3-030-53199-7
024 7 _a10.1007/978-3-030-53199-7
_2doi
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a005.74
_223
245 1 0 _aKnowledge Graphs and Big Data Processing
_h[electronic resource] /
_cedited by Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXI, 209 p. 39 illus., 32 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v12072
505 0 _aFoundations -- 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.
506 0 _aOpen Access
520 _aThis 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.
650 0 _aDatabase management.
650 0 _aApplication software.
650 0 _aLogic programming.
650 0 _aInformation technology
_xManagement.
650 0 _aBusiness information services.
650 1 4 _aDatabase Management.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aLogic in AI.
650 2 4 _aComputer Application in Administrative Data Processing.
650 2 4 _aBusiness Information Systems.
700 1 _aJanev, Valentina.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGraux, Damien.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aJabeen, Hajira.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSallinger, Emanuel.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030531980
776 0 8 _iPrinted edition:
_z9783030532000
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v12072
856 4 0 _uhttps://doi.org/10.1007/978-3-030-53199-7
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