Graph-Augmented Intelligence Engineering Series (6 Ergebnisse)

Paperback. Zustand: New.

Paperback. Zustand: new. Paperback. Graph RAG powered Systems is the definitive engineering guide to building intelligent retrieval architectures that combine knowledge graphs, vector embeddings, and large language models into unified, high-accuracy RAG workflows.This volume provides a deep, technical foundation for designing and implementing semantic retrieval systems using Neo4j, RDF, SPARQL, Cypher, and modern vector databases.Readers will learn how to construct expressive graph schemas, model relationships, unify structured and unstructured data, and design multi-hop retrieval chains that outperform traditional dense retrieval techniques. The book covers end-to-end pipeline design from ETL ingestion, ontology creation, entity canonicalization, graph cleansing, and semantic indexing to hybrid vector-graph querying, context ranking, and RAG orchestration.Included are practical engineering patterns for building domain-specific retrieval systems in finance, science, legal research, and enterprise knowledge hubs. Readers will implement workflows that ensure precision, traceability, explainability, and repeatability, creating retrieval systems suitable for mission-critical applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Zustand: New.

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Zustand: new. Paperback. Graph RAG powered Systems is the definitive engineering guide to building intelligent retrieval architectures that combine knowledge graphs, vector embeddings, and large language models into unified, high-accuracy RAG workflows.This volume provides a deep, technical foundation for designing and implementing semantic retrieval systems using Neo4j, RDF, SPARQL, Cypher, and modern vector databases.Readers will learn how to construct expressive graph schemas, model relationships, unify structured and unstructured data, and design multi-hop retrieval chains that outperform traditional dense retrieval techniques. The book covers end-to-end pipeline design from ETL ingestion, ontology creation, entity canonicalization, graph cleansing, and semantic indexing to hybrid vector-graph querying, context ranking, and RAG orchestration.Included are practical engineering patterns for building domain-specific retrieval systems in finance, science, legal research, and enterprise knowledge hubs. Readers will implement workflows that ensure precision, traceability, explainability, and repeatability, creating retrieval systems suitable for mission-critical applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.