Mastering Knowledge Graphs And Llm Integration
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Mastering Knowledge Graphs And Llm Integration
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Author : Damian Zion
language : en
Publisher: Independently Published
Release Date : 2025-11-11
Mastering Knowledge Graphs And Llm Integration written by Damian Zion and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-11 with Computers categories.
This book is a comprehensive guide to the future of intelligent systems - where Knowledge Graphs meet Large Language Models (LLMs) to create AI that understands, reasons, and explains. It explores the complete journey from foundational concepts to advanced architectures, showing how structured knowledge and neural intelligence work together to power context-aware, trustworthy, and scalable AI applications. Written with the precision of an AI researcher and the clarity of a software engineer, Mastering Knowledge Graphs and LLM Integration bridges academic theory and real-world practice. Each chapter is backed by practical code examples, real industry use cases, and proven deployment templates used in enterprise AI environments. This book delivers not just knowledge - but implementation confidence, rooted in authentic, production-tested systems. About the Technology: Knowledge Graphs provide the structured backbone of reasoning - representing entities, relationships, and context. Large Language Models bring the semantic understanding that allows systems to communicate naturally. When fused, they form a new class of hybrid AI systems capable of contextual inference, explainability, and long-term memory. The book covers modern graph frameworks (Neo4j, GraphDB, RDFLib), hybrid reasoning paradigms (SPARQL + LLMs, GraphRAG), and integration strategies that transform traditional AI workflows into explainable, cognitive systems. What's Inside: Inside these pages, you'll learn to: Design and build semantic knowledge graphs for hybrid AI reasoning. Integrate LLMs with graph databases using Python, LangChain, and Neo4j. Engineer context-aware, explainable AI pipelines for real-world applications. Deploy scalable KG-LLM systems using Docker, Kubernetes, and Helm. Evaluate factual accuracy, consistency, and explainability using advanced metrics. Every chapter includes authentic, working examples - from building your first ontology to orchestrating graph-grounded RAG pipelines for cognitive assistants. Who This Book Is For: This book is written for AI engineers, data scientists, software architects, and researchers who want to move beyond pure neural networks and build structured, intelligent systems. Whether you're designing enterprise search engines, intelligent assistants, or autonomous reasoning agents, this book will help you architect the foundations of trustworthy, graph-integrated AI. AI is shifting faster than any technology before it. Companies and researchers that adopt hybrid intelligence early - systems that can reason, explain, and adapt - will define the next decade of innovation. Staying with black-box models is no longer enough; the future belongs to explainable, structured, and self-aware AI systems. This book gives you the roadmap to build them today. This is more than a technical manual - it's a professional accelerator. Every concept, tool, and workflow in this book is geared toward building production-ready systems that deliver real business and research impact. By mastering the integration of knowledge and language, you'll position yourself at the forefront of AI innovation - where understanding meets intelligence. If you're ready to go beyond black-box AI and start building intelligent, explainable, and self-evolving systems, this is the book for you. Get your copy of Mastering Knowledge Graphs and LLM Integration today - and start shaping the architecture of tomorrow's cognitive AI.
Proceedings Of The 2024 5th International Conference On Modern Education And Information Management Icmeim 2024
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Author : Donghui Hu
language : en
Publisher: Springer Nature
Release Date : 2024-11-26
Proceedings Of The 2024 5th International Conference On Modern Education And Information Management Icmeim 2024 written by Donghui Hu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-26 with Education categories.
This book is open access. Focusing on education and information management with modernization, ICMEIM 2024 provides a platform for scholars in related fields to exchange and share information, discuss how the two affect each other, and: · Promote the modernization of education by studying certain educational issues that exist. · Open up new perspectives, broaden horizons, and examine the issues under discussion by participants. · Create a forum for sharing, research and exchange at an international level, where participants will be informed of the latest research directions, results and content in different fields, thus inspiring them to come up with new research ideas. The organizing committee of conference is delighted to invite you to participate in this exciting event, which also paves way for young researchers in acquiring knowledge and information by meeting the experts.
Knowledge Science Engineering And Management
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Author : Tianqing Zhu
language : en
Publisher: Springer Nature
Release Date : 2025-11-16
Knowledge Science Engineering And Management written by Tianqing Zhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-16 with Computers categories.
The six-volume proceedings set LNAI 15919, 15920, 15921, 15922, 15923 and 15924 constitutes the refereed proceedings of the 18th International Conference on Knowledge Science, Engineering and Management, KSEM 2025, held in Macao, China during August 4–7, 2025. The 106 papers and 66 short papers are included in these proceedings were carefully reviewed and selected from 354 submissions. They focus on all aspects of the exchange of research in artificial intelligence, data science, knowledge engineering, AI safety, large language models, and related frontier areas.
Agentic Architectural Patterns For Building Multi Agent Systems
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Author : Dr. Ali Arsanjani
language : en
Publisher: Packt Publishing Ltd
Release Date : 2026-01-23
Agentic Architectural Patterns For Building Multi Agent Systems written by Dr. Ali Arsanjani and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-23 with Computers categories.
Transform GenAI experiments into production-ready intelligent agents with scalable AI systems, architectural patterns, frameworks, and responsible AI and governance best practices Free with your book: DRM-free PDF version + access to Packt's next-gen Reader* Key Features Build robust single and multi-agent GenAI systems for enterprise use Understand the GenAI and Agentic AI maturity model and enterprise adoption roadmap Use prompt engineering and optimization, various styles of RAG, and LLMOps to enhance AI capability and performance Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative AI has moved beyond the hype, and enterprises now face the challenge of turning prototypes into scalable solutions. This book is your guide to building intelligent agents powered by LLMs. Starting with a GenAI maturity model, you’ll learn how to assess your organization’s readiness and create a roadmap toward agentic AI adoption. You’ll master foundational topics such as model selection and LLM deployment, progressing to advanced methods such as RAG, fine-tuning, in-context learning, and LLMOps, especially in the context of agentic AI. You'll explore a rich library of agentic AI design patterns to address coordination, explainability, fault tolerance, and human-agent interaction. This book introduces a concrete, hierarchical multi-agent architecture where high-level orchestrator agents manage complex business workflows by delegating entire sub-processes to specialized agents. You’ll see how these agents collaborate and communicate using the Agent-to-Agent (A2A) protocol. To ensure your systems are production-ready, we provide a practical framework for observability using life cycle callbacks, giving you the granular traceability needed for debugging, compliance, and cost management. Each pattern is backed by real-world scenarios and code examples using the open source Agent Development Kit (ADK). *Email sign-up and proof of purchase required What you will learn Apply design patterns to handle instruction drift, improve coordination, and build fault-tolerant AI systems Design systems with the three layers of the agentic stack: function calling, tool protocols (MCP), and A2A collaboration Develop responsible, ethical, and governable GenAI applications Use frameworks such as ADK, LangGraph, and CrewAI with code examples Master prompt engineering, LLMOps, and AgentOps best practices Build agentic systems using RAG, fine-tuning, and in-context learning Who this book is for This book is for AI developers, data scientists, and professionals eager to apply GenAI and agentic AI to solve business challenges. A basic grasp of data and software concepts is expected. The book offers a clear path for newcomers while providing advanced insights for individuals already experimenting with the technology. With real-world case studies, technical guides, and production-focused examples, the book supports a wide range of skill levels, from learning the foundations to building sophisticated, autonomous AI systems for enterprise use.
Challenges And Algorithms For Knowledge Discovery From Data
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Author : Matthijs van Leeuwen
language : en
Publisher: Springer Nature
Release Date : 2025-09-22
Challenges And Algorithms For Knowledge Discovery From Data written by Matthijs van Leeuwen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-22 with Computers categories.
Arno Siebes graduated in Mathematics from Utrecht University in 1983. He joined CWI in Amsterdam in 1985, and obtained his Ph.D. in 1990 from Twente University. In 2000, he joined Utrecht University, where he took up the chair for Large Distributed Databases, which was later renamed to Algorithmic Data Analysis. He supervised 15 Ph.D. students, some of whom themselves became professors. His key research work has been on data mining and inductive databases. His most impactful contribution is using the minimum description length (MDL) principle for pattern mining, the algorithm known as Krimp led to an important subdomain in data mining. Arno has been a key member of the European data mining and machine learning community. In addition to his work on the Intelligent Data Analysis symposia, he was program co-chair of the first co-located edition of the European Conference on Machine Learning (ECML) and European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) and played a key role in the development of this thriving event. Throughout his research and teaching career, Arno has maintained the philosophy that theory should work in practice. The contributions in this Festschrift serve as a reminder of his successes as a researcher and mentor. The chapters are categorized into topical sections on pattern mining, learning and reasoning, and large language models.
Computer Applications
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Author : Lan Huang
language : en
Publisher: Springer Nature
Release Date : 2026-01-20
Computer Applications written by Lan Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-20 with Computers categories.
This book CCIS 2774 constitutes the refereed proceedings of the 40th CCF National Conference of Computer Applications, CCF NCCA 2025, held in Beijing, China, during August 7–9, 2025. The 43 full papers presented in this book were carefully selected and reviewed from 269 submissions. These papers have been organized in the following topical sections: Artificial Intelligence and Applications Cyberspace Security Technology Data Science and Big Data Technology Frontier Technology Applications
Mastering Claude Ai
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Author : Ryan Dickey
language : en
Publisher: Springer Nature
Release Date : 2025
Mastering Claude Ai written by Ryan Dickey and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Artificial intelligence categories.
Unlock the power of Claude, an advanced conversational AI assistant, and integrate it into your daily professional workflows and decision-making . This book offers a clear, relatable path, regardless of your technical background, from first prompt to advanced user, through a guided, real-life learning approach that explains the AI learning curve. You'll start with an overview of Claude's capabilities. In Part I, Claude Fundamentals introduces you to Claude AI in a clear, beginner-friendly way, using relatable comparisons and real examples. It guides you through initial setup, early conversations, and key lessons learned from trial and error. The section also explores prompt design, showing how skills evolve from basic to advanced, with practical before-and-after insights. Part II dives into hands-on applications--writing, research, coding, creativity, and data analysis--demonstrating how Claude can support a wide range of professional and personal use cases. Part III then introduces advanced strategies like prompt chaining and feature optimization, while Part IV explores professional domains including business, education, and artistic collaboration. In Part V, you'll gain insights into troubleshooting, responsible AI use, and keeping up with rapid AI advancements. Finally, Part VI synthesizes the full journey, offering guidance on becoming a true power user and shaping the future of human-AI collaboration. Through transparent storytelling, tested frameworks, and actionable strategies, this practical guide will empower you to turn Claude AI from a tool into a transformative partner. What You Will Learn Use Claude AI effectively, even with no technical background or coding experience Master prompting techniques that evolve from simple queries to advanced, optimized conversations Apply Claude in writing, research, coding, creativity, and data analysis with real-life examples Explore Claude's advanced features and integrate them into daily professional workflows and decision-making Who This Book Is For Creative professionals, educators, and business leaders exploring practical AI integration. It's also ideal for entrepreneurs seeking new opportunities and knowledge workers aiming to boost productivity.
Prompt Engineering For Business
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Author : Nabil Anine
language : en
Publisher: Nabil Anine
Release Date :
Prompt Engineering For Business written by Nabil Anine and has been published by Nabil Anine this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Prompt engineering has become a core workplace skill, yet many professionals use AI tools without understanding how prompts influence outputs or how sensitive data can be exposed through careless interaction. Prompt Engineering for Business provides practical guidance for using AI safely, responsibly, and effectively in professional environments. This book focuses on real-world business use cases rather than technical theory. It helps professionals understand how to communicate with AI tools while protecting confidential information and aligning with organizational policies. Readers will learn how to: - Design effective prompts for business tasks - Avoid common data handling and privacy risks - Use AI responsibly in everyday workflows - Align AI usage with security and compliance expectations - Improve productivity without compromising trust Written in a clear and practical style, this book is designed for professionals who want to work confidently with AI while minimizing risk.
Knowledge Graphs Rag
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Author : MAXIME. LANE
language : en
Publisher: Independently Published
Release Date : 2025-02-03
Knowledge Graphs Rag written by MAXIME. LANE and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-03 with Computers categories.
Knowledge Graphs RAG: A Practical Guide to Designing and Implementing Graph-Based Systems Unlock the full potential of interconnected data with Knowledge Graphs RAG: A Practical Guide to Designing and Implementing Graph-Based Systems. This comprehensive guide is your gateway to the cutting-edge world of graph-based technologies and Retrieval-Augmented Generation (RAG). Whether you're a data scientist, software engineer, or AI enthusiast, this book provides step-by-step insights into building, implementing, and optimizing knowledge graphs and graph-enhanced RAG systems. Dive deep into the fundamentals of knowledge graphs, explore advanced techniques for integrating large language models (LLMs) with graph data, and discover how to create dynamic, contextually enriched responses using graph RAG approaches. From mastering the concepts of llm knowledge graph integration to understanding graph rag strategies, this book covers it all. Inside, you'll learn how to: Build and leverage knowledge graphs: Understand the theory and practical applications behind knowledge graphs, and learn how to create knowledge graph-enhanced RAG systems that drive intelligent decision-making. Integrate RAG with graph data: Discover how to implement knowledge graphs rag and graph rag solutions that combine traditional graph theory with state-of-the-art large language models. Master graphrag techniques: Gain expert insights into graphrag mastery and learn the secrets of mastering graphrag to build scalable, high-performance systems. Enhance search and recommendation: Use graph rag strategies to elevate your search relevance and recommendation engines, delivering personalized user experiences that adapt in real time. Explore real-world applications: From enterprise knowledge graphs to digital transformation and beyond, see how graph rag books are revolutionizing industries by connecting data in powerful new ways. Whether you're interested in graph rag, large language models graph rag, or simply want to become proficient in knowledge graph-enhanced RAG, this book is the ultimate resource for you. It seamlessly combines theory with practical applications and hands-on projects, making it a must-have for anyone looking to stay ahead in the rapidly evolving landscape of graph-based AI. Embrace the future of data with Knowledge Graphs RAG: A Practical Guide to Designing and Implementing Graph-Based Systems and join the ranks of innovators who are shaping tomorrow's technology today.
Mastering Knowledge Graphs For Llms
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Author : Mathias Sandgreen
language : en
Publisher: Independently Published
Release Date : 2024-12-14
Mastering Knowledge Graphs For Llms written by Mathias Sandgreen and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-14 with Computers categories.
Mastering Knowledge Graphs for LLMs: Building Smarter RAG Pipelines What if your AI systems could think smarter, faster, and more contextually? This groundbreaking book explores the transformative power of knowledge graphs in shaping next-generation Retrieval-Augmented Generation (RAG) pipelines. Bridging the gap between structured reasoning and generative AI, it teaches how knowledge graphs elevate large language models (LLMs) by delivering precise, context-aware, and factually grounded responses. What you'll discover: How to design and build robust knowledge graphs tailored for AI applications. Cutting-edge techniques to integrate graphs with LLMs in RAG pipelines. Real-world applications in domains like healthcare, finance, and customer service. Solutions to address key challenges like scaling, privacy, and reducing LLM hallucinations. Emerging trends and research opportunities that will shape the future of AI and knowledge graphs. Packed with actionable insights, practical advice, and clear explanations, this book is your ultimate guide to mastering the synergy between knowledge graphs and LLMs. Ready to revolutionize your AI systems? Order this essential resource and start building smarter RAG pipelines today!