Llms knowledge graphs semantic (27 résultats)

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Taschenbuch. Etat : Neu. Neuware - No more prompts. Begin grounding. Large Language Models have changed the way we interact with machines, but they have a fatal flaw for enterprise applications: they rely on statistical probability, not deterministic truth. They hallucinate facts, struggle with multi-hop reasoning, and don't have the structured logic necessary for mission-critical systems. Standard vector-based Retrieval-Augmented Generation (RAG) attempts to remedy this, but viewing data as a flat ocean of semantic similarity is not enough. To build AI that actually knows, AI that is verifiable, explainable, and trustworthy, you must move from flat data to interconnected data. You want knowledge graph. This is your architectural blueprint for the next 10 years of artificial intelligence. This book will teach you how to build neuro-symbolic artificial intelligence systems that bridge the gap between deep learning and semantic web technologies, bringing the linguistic fluency of LLMs together with the rigorous, deterministic logic of Knowledge Graphs. Whether you're trying to remove hallucinations from your company's internal chatbot or designing autonomous AI agents that can handle complex enterprise data, this book provides the theoretical foundation and the production-ready code you need to succeed.- What You'll LearnGraph Data Foundations: Understand domain-driven design for scalable ontologies, and transform messy data into structured graph databases. Automated Knowledge Extraction Use LLMs, Named Entity Recognition (NER) and relationship extraction to automatically build Knowledge Graphs from unstructured text, PDFs and documents. GraphRAG: Go beyond traditional vector search. Design hybrid retrieval pipelines enabling true multi-hop reasoning using semantic embeddings and topological graph traversal. Machine Learning on Graphs: Leverage Graph Neural Networks (GNNs), node classification, and link prediction to discover hidden insights and structural patterns your LLM cannot infer itself. Create Autonomous AI Agents: Build end-to-end agents that leverage your Knowledge Graph as a map of the environment to drive memory, multi-step planning and autonomous decision-making. Production Deployment: Scale, secure, and govern knowledge-aware artificial intelligence systems in an enterprise setting.- Who This Book Is ForThis book is written for software engineers, data scientists, AI researchers, and technical architects ready to take their work beyond simple API wrappers. If you know Python, and understand databases and LLMs at a basic level, you have all you need to start building intelligent, graph-powered systems. The future of AI is not strictly neural. It's neuro-symbolic. Learn to build systems that don't just talk, but understand.…

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Paperback. Etat : new. Paperback. In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Etat : new. Paperback. In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Etat : new. Hardcover. In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Etat : new. Hardcover. In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Etat : new. Paperback. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists.…

Taschenbuch. Etat : Neu. LLMs, Knowledge Graphs, and the Semantic Web | Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities | Fernando Ortiz-Rodriguez (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337313610 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Hardcover. Etat : new. Hardcover. In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Etat : Neu. LLMs, Knowledge Graphs, and the Semantic Web | Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities | Fernando Ortiz-Rodriguez (u. a.) | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337313603 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists.…