Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Graph Data Science with Neo4j

You're reading from   Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Arrow left icon
Product type Paperback
Published in Jan 2023
Publisher Packt
ISBN-13 9781804612743
Length 288 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Estelle Scifo Estelle Scifo
Author Profile Icon Estelle Scifo
Estelle Scifo
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1 – Creating Graph Data in Neo4j
2. Chapter 1: Introducing and Installing Neo4j FREE CHAPTER 3. Chapter 2: Importing Data into Neo4j to Build a Knowledge Graph 4. Part 2 – Exploring and Characterizing Graph Data with Neo4j
5. Chapter 3: Characterizing a Graph Dataset 6. Chapter 4: Using Graph Algorithms to Characterize a Graph Dataset 7. Chapter 5: Visualizing Graph Data 8. Part 3 – Making Predictions on a Graph
9. Chapter 6: Building a Machine Learning Model with Graph Features 10. Chapter 7: Automatically Extracting Features with Graph Embeddings for Machine Learning 11. Chapter 8: Building a GDS Pipeline for Node Classification Model Training 12. Chapter 9: Predicting Future Edges 13. Chapter 10: Writing Your Custom Graph Algorithms with the Pregel API in Java 14. Index 15. Other Books You May Enjoy

Characterizing a graph from its node and edge properties

There is not a single type of graph. Each of them has specific characteristics, depending on the modeled process. This section describes some of the characteristics of a graph you should question when starting your journey with a new dataset.

Link direction

Links between nodes can be directed (and are then called arcs in graph theory) or undirected (and are called edges).

While graph theory makes the distinction between directed and undirected links in their naming, the graph database vocabulary usually doesn’t, and all links are called edges or relationships, regardless of whether they’re considered directed or not. In a more general way, I’ll stick to the wording used within the Neo4j Graph Data Science Library, which may sound inaccurate to graph theorists.

Undirected graphs include the following:

  • Facebook social network: If you are connected to X, X is also connected to you.
  • Co...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime