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Hands-On Graph Analytics with Neo4j

You're reading from   Hands-On Graph Analytics with Neo4j Perform graph processing and visualization techniques using connected data across your enterprise

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781839212611
Length 510 pages
Edition 1st Edition
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Author (1):
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Estelle Scifo Estelle Scifo
Author Profile Icon Estelle Scifo
Estelle Scifo
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Graph Modeling with Neo4j
2. Graph Databases FREE CHAPTER 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

Introducing the Graph Data Science plugin

We'll start by introducing the GDS plugin. Provided by Neo4j, it extends the capabilities of its graph database for analytics purposes. In this section, we will go through naming conventions and introduce the very important concept of graph projection, which we will use intensively in the rest of this book.

The first implementation of this plugin was done in the Graph Algorithms library, which was first released in June 2017. In 2020, it was replaced by the GDS plugin. The GDS plugin includes performance optimization for the most used algorithms so that they can run on huge graphs (several billions of nodes). Even though I will be highlighting the optimized algorithms in this book, I would suggest you refer to the latest documentation to ensure you get the most up-to-date information (https://neo4j.com/docs/graph-data-science/current/).

The full code of the GDS plugin is open source and available on GitHub at: https://github.com/neo4j/graph...
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