Ebook: Building Knowledge Graphs: A Practitioner’s Guide (6th Early Release)

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 saving interlinked descriptions of entities (objects, events, situations, or abstract concepts) while encoding the semantics underlying the terminology. How do you create a knowledge graph? And how do you move it from theory into practice?

Graph data has become ubiquitous in the last decade. Graphs underpin everything from consumer-facing systems like navigation and social networks to critical infrastructure like supply chains and policing. A consistent theme has emerged: applying knowledge in context is the single most powerful tool that most businesses have. Through research and experience, a set of patterns and practices called knowledge graphs has been developed to support extracting knowledge from data of all types and in all sources, from systems of record to frozen data lakes to application logs. This book is for information technology professionals who are interested in building and operating knowledge graphs within their businesses.

Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa, Maya Natarajan, and Jim Webber from Neo4j illustrate patterns commonly used for building knowledge graphs that solve many of today’s pressing problems. You’ll quickly discover how these graphs become exponentially more useful as you add more data.

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
Understand what pattern detection knowledge graphs help you accomplish
Explore dependency knowledge graphs through examples
Use examples of natural language knowledge graphs and chatbots