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28.2 MB
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8249B8C31CE801D7706899FD7EF910802B08758A
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July 25, 2025, 8:55 a.m.
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(Last updated: July 25, 2025, 8:56 a.m.)
| File | Size |
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| Negro A. Knowledge Graphs and LLMs in Action (MEAP v11) 2025.pdf | 28.2 MB |
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28.2 MB
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| Uploaded by andryold1 | Size 28.2 MB | Health [ 20 /16 ] | Added 2025-07-25 |
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| Uploaded by indexFroggy | Size 14.6 MB | Health [ 14 /3 ] | Added 2025-01-02 |
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SOURCE: Negro A. Knowledge Graphs and LLMs in Action (MEAP v11) 2025
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COVER
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MEDIAINFO
Textbook in PDF format Knowledge graphs help understand relationships between the objects, events, situations, and concepts in your data so you can readily identify important patterns and make better decisions. This book provides tools and techniques for efficiently labeling data, modeling a knowledge graph, and using it to derive useful insights. In Knowledge Graphs and LLMs in Action you will learn how to Model knowledge graphs with an iterative top-down approach based in business needs Create a knowledge graph starting from ontologies, taxonomies, and structured data Use machine learning algorithms to hone and complete your graphs Build knowledge graphs from unstructured text data sources Reason on the knowledge graph and apply machine learning algorithms Move beyond analyzing data and start making decisions based on useful, contextual knowledge. The cutting-edge knowledge graphs (KG) approach puts that power in your hands. In Knowledge Graphs and LLMs in Action, you’ll discover the theory of knowledge graphs and learn how to build services that can demonstrate intelligent behavior. You’ll learn to create KGs from first principles and go hands-on to develop advisor applications for real-world domains like healthcare and finance. Knowledge Graphs and LLMs in Action Preface Part_I:_Foundations_of_hybrid_intelligent_systems Knowledge_graphs_and_LLMs:_a_killer_combination Intelligent_systems:_a_hybrid_approach Part_II:_Building_knowledge_graphs_from_structured_data_sources Create_your_first_Knowledge_Graph_from_ontologies From_simple_networks_to_multi-source_integration Part_III:_Building_knowledge_graphs_from_text Domain-specific_knowledge_extraction_from_unstructured_data Building_knowledge_graphs_with_large_language_models Named_entity_disambiguation NED_with_open_LLMs_and_domain_ontologies Part_IV:_Machine_learning_on_knowledge_graphs Machine_learning_on_knowledge_graphs:_a_primer_approach Graph_feature_engineering:_manual_and_semi automated_approaches Graph_representation_learning_and_graph_neural_network Node_classification_and_link_prediction_with_GNNs Part_V:_Information_retrieval_with_knowledge_graphs_and_LLMs Knowledge_graph-powered_retrieval_augmented_generation Ask_a_KG_with_natural_language Building_a_QA_agent_with_LangGraph Appendix_A._Introduction_to_graphs Appendix_B._Neo4j Appendix_C._Build_knowledge_graphs_from_structured_sources
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