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010   $a9783031452567$b(electronic bk.)
010   $z9783031452550
024 7 $a10.1007/978-3-031-45256-7
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101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 13$aAn Introduction to Knowledge Graphs /$fby Umutcan Serles, Dieter Fensel
205   $a1st ed. 2024.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024.
215   $a1 online resource (440 pages)
311 08$aPrint version: Serles, Umutcan An Introduction to Knowledge Graphs Cham : Springer,c2024 9783031452550 
327   $aPart I: Knowledge Technology in Context -- 2. Introduction -- 3. Information Retrieval and Hypertext -- 4. The Internet -- 5. The World Wide Web -- 6. Natural Language Processing -- 7. Semantic Web ? Or AI Revisited -- 8. Databases -- 9. Web of Data -- 10. Knowledge Graphs -- Part II: Knowledge Representation -- 11. Introduction to Knowledge Representation -- 12. The Five Levels of Representing Knowledge -- 13. Epistemology -- 14. The Logical Level -- 15. Analysis of Schema.org at Five Levels of KR -- 16. Summary -- Part III: Knowledge Modeling -- 17. Introduction: The Overall Model -- 18. Knowledge Creation -- 19. Knowledge Hosting -- 20. Knowledge Assessment -- 21. Knowledge Cleaning -- 22. Knowledge Enrichment -- 23. Tooling and Knowledge Deployment -- 24. Summary -- Part IV: Applications -- 25. Applications.
330   $aThis textbook introduces the theoretical foundations of technologies essential for knowledge graphs. It also covers practical examples, applications and tools. Knowledge graphs are the most recent answer to the challenge of providing explicit knowledge about entities and their relationships by potentially integrating billions of facts from heterogeneous sources. The book is structured in four parts. For a start, Part I lays down the overall context of knowledge graph technology. Part II ?Knowledge Representation? then provides a deep understanding of semantics as the technical core of knowledge graph technology. Semantics is covered from different perspectives, such as conceptual, epistemological and logical. Next, Part III ?Knowledge Modelling? focuses on the building process of knowledge graphs. The book focuses on the phases of knowledge generation, knowledge hosting, knowledge assessment, knowledge cleaning, knowledge enrichment, and knowledge deployment to cover a complete life cycle for this process. Finally, Part IV (simply called ?Applications?) presents various application areas in detail with concrete application examples as well as an outlook on additional trends that will emphasize the need for knowledge graphs even stronger. This textbook is intended for graduate courses covering knowledge graphs. Besides students in knowledge graph, Semantic Web, database, or information retrieval classes, also advanced software developers for Web applications or tools for Web data management will learn about the foundations and appropriate methods.
606   $aArtificial intelligence
606   $aInformation storage and retrieval systems
606   $aExpert systems (Computer science)
606   $aNatural language processing (Computer science)
606   $aArtificial Intelligence
606   $aInformation Storage and Retrieval
606   $aKnowledge Based Systems
606   $aNatural Language Processing (NLP)
615  0$aArtificial intelligence.
615  0$aInformation storage and retrieval systems.
615  0$aExpert systems (Computer science)
615  0$aNatural language processing (Computer science)
615 14$aArtificial Intelligence.
615 24$aInformation Storage and Retrieval.
615 24$aKnowledge Based Systems.
615 24$aNatural Language Processing (NLP).
676   $a001.4226
700   $aSerles$b Umutcan$01742037
701   $aFensel$b Dieter$0542875
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910865249903321
996   $aAn Introduction to Knowledge Graphs$94168655
997   $aUNINA