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

Defining importance

Determining the most important node of a graph depends on your definition of importance. This definition itself depends on the goal you are trying to achieve. In this chapter, we will study two examples of importance:

  • Information spread within a social network
  • Critical nodes in a road or computer network

We will learn that each of these problems can be tackled with centrality algorithms. In this section, we will consider the following graph as an example to help us understand the different definitions of importance:

Which node is the most important in this network? The answer depends on what important means in a given context. Let's consider the different ways of defining importance.

Popularity and information spread

The most obvious way to define importance is with the influencer concept. Most influential nodes have many connections and, as such, are well placed to spread information. In the context of social networks, influencers often get offered advertising...