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Graph Data Science with Neo4j

You're reading from  Graph Data Science with Neo4j

Product type Book
Published in Jan 2023
Publisher Packt
ISBN-13 9781804612743
Pages 288 pages
Edition 1st Edition
Languages
Author (1):
Estelle Scifo Estelle Scifo
Profile icon Estelle Scifo

Table of Contents (16) Chapters

Preface 1. Part 1 – Creating Graph Data in Neo4j
2. Chapter 1: Introducing and Installing Neo4j 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

Computing the graph degree distribution

After the number of nodes and edges, the node’s degree is one of the first metrics to compute when studying a new graph. It tells us whether the edges are equally split across nodes or if some nodes monopolize almost all connections, leaving the others disconnected. Now that we’ve defined the node’s degree, we will learn how to compute it with Cypher and draw the distribution using the NeoDash graph application.

Definition of a node’s degree

The degree of a node is the number of links connected to this node. For undirected graphs, there is only one degree, since we just count all the edges connected to a given node. For directed graphs, we can compute the node’s degree in three different ways:

  • Incoming degree: We count only the edges pointing toward the node
  • Outgoing degree: We count only the edges pointing outward of the node
  • Total degree: We count all edges attached to a node, regardless...
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