Applied Knowledge Graph Engineering for LLMs
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Home > Computing and Information Technology > Computer science > Mathematical theory of computation > Applied Knowledge Graph Engineering for LLMs: From Design to Deployment of Context-Aware Graph Systems
Applied Knowledge Graph Engineering for LLMs: From Design to Deployment of Context-Aware Graph Systems

Applied Knowledge Graph Engineering for LLMs: From Design to Deployment of Context-Aware Graph Systems


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About the Book

What happens when structured knowledge meets intelligent language? In an era where artificial intelligence is redefining how we reason, search, and build systems, Applied Knowledge Graph Engineering for LLMs reveals how to design, connect, and deploy context-aware graph systems that power the next generation of intelligent applications. This book bridges two worlds: Knowledge Graphs (KGs) and Large Language Models (LLMs), showing engineers, researchers, and data professionals how to combine symbolic structure with neural intelligence. From graph modeling and ontology design to LangChain integration, GraphRAG retrieval, and enterprise deployment, it transforms theory into applied engineering. Inside, readers will explore: Foundations of Knowledge Graph Design: Build meaningful graph structures using RDF, OWL, and ontology best practices. Building and Querying Graphs: Construct scalable KGs from text, data, and APIs using SPARQL, GraphQL, and Cypher. Connecting Graphs to LLMs: Implement Graph-RAG pipelines with LangChain, LlamaIndex, and vector databases for context-enriched AI. Inference and Reasoning: Combine symbolic logic and machine learning to enable fact-checking and explainable AI. Deployment and Optimization: Architect, scale, and monitor graph-based systems in real-world production environments. Practical Case Studies: Learn from domain-tested applications in healthcare, finance, cybersecurity, and enterprise AI. Unlike traditional AI or database guides, this book provides an end-to-end framework from graph design to production-level deployment, with actionable workflows and best practices grounded in real systems. Whether you're integrating Neo4j with an LLM, modeling enterprise ontologies, or deploying retrieval-augmented chat systems, this book offers the technical clarity and structure you need. If you've ever wondered how to make LLMs think with context, this is your blueprint. Get your copy of Applied Knowledge Graph Engineering for LLMs by Ted Wayne today and start building intelligent systems that reason, retrieve, and respond with true understanding.


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Product Details
  • ISBN-13: 9798270999032
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 164
  • Returnable: N
  • Sub Title: From Design to Deployment of Context-Aware Graph Systems
  • Width: 178 mm
  • ISBN-10: 8270999032
  • Publisher Date: 21 Oct 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 9 mm
  • Weight: 349 gr


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