Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecuritythreat intelligence, GDPR compliance, web user engagement, and much more.
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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?
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Using hands-on examples, this practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors JesĂşs Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of todayâs pressing knowledge management problems. Youâll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning.
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⢠Learn knowledge graph organizing principles
⢠Exploregraph databases and knowledgegraphs ⢠Import structured and unstructured data
⢠Build integration-and-search knowledge graphs
⢠Discover pattern detection knowledge graphs
⢠Use natural languageknowledge graphs and chatbots
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