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Hands-On Graph Analytics with Neo4j

You're reading from  Hands-On Graph Analytics with Neo4j

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781839212611
Pages 510 pages
Edition 1st Edition
Languages
Author (1):
Estelle Scifo Estelle Scifo
Profile icon Estelle Scifo
Toc

Table of Contents (18) Chapters close

Preface 1. Section 1: Graph Modeling with Neo4j
2. Graph Databases 3. The Cypher Query Language 4. Empowering Your Business with Pure Cypher 5. Section 2: Graph Algorithms
6. The Graph Data Science Library and Path Finding 7. Spatial Data 8. Node Importance 9. Community Detection and Similarity Measures 10. Section 3: Machine Learning on Graphs
11. Using Graph-based Features in Machine Learning 12. Predicting Relationships 13. Graph Embedding - from Graphs to Matrices 14. Section 4: Neo4j for Production
15. Using Neo4j in Your Web Application 16. Neo4j at Scale 17. Other Books You May Enjoy

Summary

In this chapter, you learned how to navigate into your Neo4j graph. You are now able to perform CRUD operations with Cypher, creating, updating, and deleting nodes, relationships, and their properties.

But the full power of Neo4j lies in relationship traversal (going from one node to its neighbors is super fast) and pattern matching you are now able to perform with Cypher.

You have also discovered how to measure your query performance with the Cypher query planner. This can help you to avoid some pitfalls, such as the Eager operation when loading data. It will also help in understanding Cypher internals and tuning your query for better performance in terms of speed.

We know have all the tools in hand to start really using Neo4j and study some real-life examples. In the next chapter, we will learn about knowledge graphs. For many organizations, this is the first entry point to the world of graphs. With that data structure, we will be able to implement performant recommendation...

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