Building Knowledge Graphs A Practitioner S Guide Pdf Github
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The Routledge Companion to Artificial Intelligence in Architecture
Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference.
Building Knowledge Graphs
Author: Jesus Barrasa
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-06-22
Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities—objects, events, situations, or abstract concepts—and encoding the underlying information. How do you create a knowledge graph? And how do you move it from theory into production? Using hands-on examples, this practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors Jesús Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of today’s pressing knowledge management problems. You’ll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning. Learn the organizing principles necessary to build a knowledge graph Explore how graph databases serve as a foundation for knowledge graphs Understand how to import structured and unstructured data into your graph Follow examples to build integration-and-search knowledge graphs Learn what pattern detection knowledge graphs help you accomplish Explore dependency knowledge graphs through examples Use examples of natural language knowledge graphs and chatbots Use graph algorithms and ML to gain insight into connected data
Designing and Building Enterprise Knowledge Graphs
Author: Juan Sequeda
language: en
Publisher: Morgan & Claypool Publishers
Release Date: 2021-08-05
This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice. It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.