Copyright © 2019 Neo4j, Inc.

License: Creative Commons 4.0

The Graph Algorithms library has been deprecated, please see the Graph Data Science (GDS) docs. |

This is the user guide for Neo4j Graph Algorithms version 3.5, authored by the Neo4j Team.

The guide covers the following areas:

- Chapter 1,
*Introduction*— An introduction to Neo4j Graph Algorithms. - Chapter 2,
*Projected Graph Model*— A detailed guide to the projected graph model. - Chapter 3,
*The Yelp example*— An illustration of how to use graph algorithms on a social network of friends. - Chapter 4,
*Procedures*— A list of Neo4j Graph Algorithm procedures. - Chapter 5,
*Centrality algorithms*— A detailed guide to each of the centrality algorithms, including use-cases and examples. - Chapter 6,
*Community detection algorithms*— A detailed guide to each of the community detection algorithms, including use-cases and examples. - Chapter 7,
*Graph similarity algorithms*— A detailed guide to each of the similarity detection algorithms, including use-cases and examples. - Chapter 8,
*Auxiliary procedures*— A detailed guide to each of the auxiliary procedures, including use-cases and examples.

In addition to the above algorithms, there are a large number of algorithm implementations developed as part of Neo4j Labs.
These include algorithms in various categories, including categories in which there are officially supported algorithms.
The Neo4j Labs algorithms are documented in Chapter 9, *Neo4j Labs Graph Algorithms*.
Please note that Neo4j Labs algorithms are not supported for production purposes.

Graph Algorithms: Practical Examples in Apache Spark and Neo4j, by Mark Needham & Amy E. Hodler and published by O’Reilly Media is available now.

Download it for free at neo4j.com/graph-algorithms-book/.