Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Graph-RAG Engineering: Integrating Knowledge Graphs with LLMs for Context-Aware AI: Design Patterns, Graph Modeling, SPARQL & Neo4j Workflows, and Gra

Graph-RAG Engineering: Integrating Knowledge Graphs with LLMs for Context-Aware AI: Design Patterns, Graph Modeling, SPARQL & Neo4j Workflows, and Gra

Zhu, Yuan

Paperback

Series: Agentic AI and Graph-Powered Workflows Series: Practical Guides to Multi-Agent Systems, Langflow, R, Book 4

General Computers

ISBN13: 9798262670468
Publisher: Independently Published
Published: Aug 28 2025
Pages: 428
Weight: 1.63
Height: 0.87 Width: 7.00 Depth: 10.00
Language: English
Graph-RAG Engineering shows how to combine structured knowledge from Knowledge Graphs with Large Language Models to build context-aware, explainable, and high-precision AI applications. The book covers graph modeling (RDF, property graphs), building and maintaining knowledge graphs with Neo4j/RDFLib, querying with SPARQL and Cypher, and creating Graph-RAG pipelines that fuse graph retrieval with dense vector search. Learn multi-hop reasoning, graph neural networks (GNN) for link prediction and entity disambiguation, temporal and streaming graph updates, and strategies for keeping graphs consistent and fresh. Practical projects include personalized recommendation systems, scientific discovery assistants, legal & regulatory search, and enterprise knowledge hubs. The book also addresses schema design, entity linking, provenance, versioning, and production considerations (ETL, connectors, monitoring).

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