Book Image

Hands-On Graph Analytics with Neo4j

By : Estelle Scifo
Book Image

Hands-On Graph Analytics with Neo4j

By: Estelle Scifo

Overview of this book

Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data.
Table of Contents (18 chapters)
1
Section 1: Graph Modeling with Neo4j
5
Section 2: Graph Algorithms
10
Section 3: Machine Learning on Graphs
14
Section 4: Neo4j for Production

Introducing community detection and its applications

Community detection gathers techniques that have been developed to understand the structure of a graph and extract information from it. This structure can then be used in many applications, such as recommendation engines, fraud detection, property prediction, and link prediction.

Throughout this chapter, I will use the words community, cluster, or partition to refer to a group of nodes sharing common properties.

Identifying clusters of nodes

The following image shows the graph of Neo4j GitHub users we built in Chapter 2, The Cypher Query Language. Community detection algorithms were able to identify several communities:

Image generated using the Louvain algorithm and neoviz.js

By the end of this chapter, you will be able to reproduce this image. Further analysis will be needed to understand the common properties of the users belonging to the violet community. A deeper analysis of this graph teaches us that the users in the violet community...