NEXT- GEN AI WITH KNOWLEDGE GRAPHS AND LLMs (Paperback)
Language: English
Published by Independently Published, 2025
- Softcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
£ 16.24
Quantity: 1 available
Add to basketItem description from seller
Paperback. Next-Gen AI with Knowledge Graphs and LLMs is a comprehensive guide to building intelligent systems that combine symbolic reasoning with modern language models. As AI continues to evolve beyond simple text prediction, the future belongs to systems that understand context, model relationships, manage domain knowledge, and deliver reliable, explainable results. This book shows you how Knowledge Graphs and Large Language Models can be integrated to create powerful hybrid intelligence. Designed for AI engineers, data scientists, architects, and advanced practitioners, this book explains how structured knowledge, graph processing, and LLM understanding can be combined to achieve accuracy, consistency, traceability, and explainability in production environments. You will learn how to connect language models to knowledge bases, use graph reasoning to correct hallucinations, design retrieval workflows, and build robust pipelines that transform LLMs into trustworthy enterprise tools. Through detailed explanations and practical insights, the book covers semantic modeling, ontology design, graph storage, query systems, RAG pipelines, hybrid reasoning strategies, agentic orchestration, and knowledge-grounded workflows. It demonstrates how to engineer modern AI systems that support decision-making, automate tasks, and deliver verifiable answers that align with real-world constraints. Inside, you will learn how to: Design and structure Knowledge Graphs for enterprise-level intelligence. Connect LLMs to structured knowledge for context-rich reasoning. Reduce hallucinations through grounding, constraints, and graph-validated retrieval. Implement hybrid RAG architectures that leverage symbolic and neural intelligence. Use graph queries, embeddings, and relationships to strengthen factual accuracy. Build explainable intelligent systems that reveal their reasoning paths. Deploy scalable, maintainable, and auditable AI pipelines. Whether you are building recommendation engines, enterprise assistants, decision-support systems, automated research agents, or high-stakes AI workflows, this book gives you the foundation needed to create systems that are intelligent, reliable, and explainable. It is your guide to the next generation of AI engineering. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …
Seller Inventory # 9798277128701
- Title
- NEXT- GEN AI WITH KNOWLEDGE GRAPHS AND LLMs (Paperback)
- Author
- Leo Hartmann
- Publisher
- Independently Published
- Publication year
- 2025
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798277128701
Designed for AI engineers, data scientists, architects, and advanced practitioners, this book explains how structured knowledge, graph processing, and LLM understanding can be combined to achieve accuracy, consistency, traceability, and explainability in production environments. You will learn how to connect language models to knowledge bases, use graph reasoning to correct hallucinations, design retrieval workflows, and build robust pipelines that transform LLMs into trustworthy enterprise tools.
Through detailed explanations and practical insights, the book covers semantic modeling, ontology design, graph storage, query systems, RAG pipelines, hybrid reasoning strategies, agentic orchestration, and knowledge-grounded workflows. It demonstrates how to engineer modern AI systems that support decision-making, automate tasks, and deliver verifiable answers that align with real-world constraints.
Inside, you will learn how to:
Design and structure Knowledge Graphs for enterprise-level intelligence.
Connect LLMs to structured knowledge for context-rich reasoning.
Reduce hallucinations through grounding, constraints, and graph-validated retrieval.
Implement hybrid RAG architectures that leverage symbolic and neural intelligence.
Use graph queries, embeddings, and relationships to strengthen factual accuracy.
Build explainable intelligent systems that reveal their reasoning paths.
Deploy scalable, maintainable, and auditable AI pipelines.
Whether you are building recommendation engines, enterprise assistants, decision-support systems, automated research agents, or high-stakes AI workflows, this book gives you the foundation needed to create systems that are intelligent, reliable, and explainable. It is your guide to the next generation of AI engineering.
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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