Synopsis
Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities--objects, events, situations, or abstract concepts---and encoding the underlying information. How do you create a knowledge graph? And how do you move it from theory into production?
Using hands-on examples, this practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors Jesus Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of today's pressing knowledge management problems. You'll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning.
- Learn the organizing principles necessary to build a knowledge graph
- Explore how graph databases serve as a foundation for knowledge graphs
- Understand how to import structured and unstructured data into your graph
- Follow examples to build integration-and-search knowledge graphs
- Learn what pattern detection knowledge graphs help you accomplish
- Explore dependency knowledge graphs through examples
- Use examples of natural language knowledge graphs and chatbots
- Use graph algorithms and ML to gain insight into connected data
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos des auteurs
Dr. Jesus Barrasa, an expert in semantic technologies and graph databases, is head of the solutions architecture team in EMEA at Neo4j and leads the development of neosemantics (a Neo4j plugin for RDF). He cowrote Knowledge Graphs: Data in Context for Responsive Businesses (O'Reilly) and is cohost of the Going Meta live webcast.
Dr. Jim Webber is chief scientist at Neo4j, where he works on fault-tolerant graph databases. He coauthored Graph Databases for Dummies (Wiley) and Graph Databases and Knowledge Graphs: Data in Context for Responsive Businesses, both for O'Reilly. He's also a visiting professor at Newcastle University, UK.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by saving interlinked descriptions of entities (objects, events, situations, or abstract concepts) while encoding the semantics underlying the terminology. How do you create a knowledge graph? And how do you move it from theory into practice?Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa and Jim Webber from Neo4j illustrate patterns commonly used for building knowledge graphs that solve many of today's pressing problems. You'll quickly discover how these graphs become exponentially more useful as you add more data.Learn the organizing principles necessary to build a knowledge graphExplore how graph databases serve as a foundation for knowledge graphsUnderstand how to import structured and unstructured data into your graphFollow examples to build integration-and-search knowledge graphsUnderstand what pattern detection knowledge graphs help you accomplishExplore dependency knowledge graphs through examplesUse examples of natural language knowledge graphs and chatbots. N° de réf. du vendeur LU-9781098127107
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Paperback. Etat : new. Paperback. Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by saving interlinked descriptions of entities (objects, events, situations, or abstract concepts) while encoding the semantics underlying the terminology. How do you create a knowledge graph? And how do you move it from theory into practice? Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa, Maya Natarajan, and Jim Webber from Neo4j illustrate patterns commonly used for building knowledge graphs that solve many of today's pressing problems. You'll quickly discover how these graphs become exponentially more useful as you add more data. Learn the organizing principles necessary to build a knowledge graph Explore how graph databases serve as a foundation for knowledge graphs Understand how to import structured and unstructured data into your graph Follow examples to build integration-and-search knowledge graphs Understand what pattern detection knowledge graphs help you accomplish Explore dependency knowledge graphs through examples Use examples of natural language knowledge graphs and chatbots" Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa and Jim Webber from Neo4j illustrate patterns commonly used for building knowledge graphs that solve many of today's pressing problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781098127107
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Paperback. Etat : New. Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by saving interlinked descriptions of entities (objects, events, situations, or abstract concepts) while encoding the semantics underlying the terminology. How do you create a knowledge graph? And how do you move it from theory into practice?Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa and Jim Webber from Neo4j illustrate patterns commonly used for building knowledge graphs that solve many of today's pressing problems. You'll quickly discover how these graphs become exponentially more useful as you add more data.Learn the organizing principles necessary to build a knowledge graphExplore how graph databases serve as a foundation for knowledge graphsUnderstand how to import structured and unstructured data into your graphFollow examples to build integration-and-search knowledge graphsUnderstand what pattern detection knowledge graphs help you accomplishExplore dependency knowledge graphs through examplesUse examples of natural language knowledge graphs and chatbots. N° de réf. du vendeur LU-9781098127107
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