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

The steps toward graph machine learning

Neo4j is primarily a database and can be used as such to fetch data. However, a change of perspective is needed to express the data as a graph, as well as to exploit this graph structure by using graph algorithms and formulating the problem as a graph problem.

Building a (knowledge) graph

When beginning to build a graph out of a dataset, the main question to ask is what are the relationships that exist in this data? If we consider the CSV file we studied in the previous section alone, it does not contain a lot of information about relationships since it only has aggregated data, such as the number of followers per user.

To learn more about relationships in the data, we will have to enrich this dataset. This can be done in two ways. Either we can use an external data source as we did in Chapter 3, Empowering Your Business with Pure Cypher, or we can transform the way we see our relational data.

Creating relationships from existing data

Data can come...