Showing results for "Linked Data and Knowledge Graph English"

What if the most important information in your data lies not in individual rows and columns, but in the connections between them? Graph machine learning helps uncover patterns hidden in these relationships.Graph Machine Learning Essentials is a practical and accessible guide to understanding how machine learning works with graph-structured data, where entities are connected through relationships.Designed for software engineers, ML engineers, data scientists, resear...

Practical approaches to leveraging graph data science to solve real-world challenges. Key Features ● Explore the fundamentals of graph data science, its importance, and applications. ● Learn how to set up Python and Neo4j environments for graph data analysis. ● Discover techniques to visualize complex graph networks for better understanding. Book Description Graph Data Science with Python and Neo4j is your ultimate guide to unleashing the potential of graph data science by blending Python’...

Practical approaches to leveraging graph data science to solve real-world challenges.Key Features● Explore the fundamentals of graph data science, its importance, and applications.● Learn how to set up Python and Neo4j environments for graph data analysis.● Discover techniques to visualize complex graph networks for better understanding.Book DescriptionGraph Data Science with Python a...

The transformative impact of emerging technologies such as AI, blockchain, and machine learning on industries and societies, particularly in Africa, can drive sustainable development, improve governance, and address global challenges like climate change, economic inequality, and data privacy. Knowledge Graph and Semantic Web Technology based XAI offers readers a comprehensive study of these developments. Through real-world examples and practical insights, it demonstrates how AI an...

Learn how to build and query graph databases with this first comprehensive guide to ISO-standard GQL, featuring 50+ hands-on examples and a real-world case study that will change the way you work with connected data Free with your book: DRM-free PDF version + access to Packt's next-gen Reader\*Key FeaturesGo beyond theory and apply key concepts and syntax through interactive tutorials and practical examples via the GQL PlaygroundLeverage advanced featur...

Practical approaches to leveraging graph data science to solve real-world challenges.Key Features● Explore the fundamentals of graph data science, its importance, and applications.● Learn how to set up Python and Neo4j environments for graph data analysis.● Discover techniques to visualize complex graph networks for better understanding.Book DescriptionGraph Data Science with Python and Neo4j is your ultimate guide to unleashing the potential of ...

This book provides a coherent and unifying view for logic and representation learning to contribute to knowledge graph (KG) reasoning and produce better computational tools for integrating both worlds. To this end, logic and deep neural network models are studied together as integrated models of computation. This book is written for readers who are interested in KG reasoning and the new perspective of neuro-symbolic integration and have prior knowledge to neural networks and deep learning....

This book explores various aspects of knowledge graph reasoning to solve different tasks, encompassing first, traditional symbolic methods for knowledge graph reasoning; second, recent developments in neural-based knowledge graph reasoning techniques; and third, cutting-edge advancements in neural-symbolic hybrid approaches to knowledge graph reasoning. The authors focus on the model and algorithm design aspect and study knowledge graphs from two perspectives: background knowledge graph an...

This book constitutes the refereed proceedings of the first China Conference on Knowledge Graph and Semantic Computing, CCKS, held in Beijing, China, in September 2016.The 19 revised full papers presented together with 6 shared tasks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on knowledge representation and learning; knowledge graph construction and information extraction; linked data and knowledge-based systems; sha...

Wring more out of the data with a scientific approach to analysisGraph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations ...

This book constitutes the refereed proceedings of the 7th China Conference on Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy, CCKS 2022, in Qinhuangdao, China, August 24–27, 2022.The 15 full papers and 2 short papers included in this book were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: knowledge representation and reasoning; knowledge acquisition and knowledge base construction; lin...

This book constitutes the joint refereed proceedings of the 18th China Conference on Knowledge Graph and Semantic Computing and the 13th International Joint Conference on Knowledge Graphs, CCKS-IJCKG 2024, held in Chongqing, China, during September 20–22, 2024.The 30 full papers and 11 other papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in the following topical sections: Knowledge representation and reasoning; Knowledg...