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

Dijkstra's shortest paths algorithm

Dijkstra's algorithm was developed by the Dutch computer scientist E. W. Dijkstra in the 1950s. Its purpose is to find the shortest path between two nodes in a graph. The first subsection will guide you through how the algorithm works. The second subsection will be dedicated to the use of Dijkstra's algorithm within Neo4j and the GDS plugin.

Understanding the algorithm

Dijkstra's algorithm is probably the most famous path finding algorithm. It is a greedy algorithm that will traverse the graph breadth first (see the following figure), starting from a given node (the start node) and trying to make the optimal choice regarding the shortest path at each step:

Graph traversal (reminder from Chapter 1, Graph Databases)

In order to understand the algorithm, let's run it on a simple graph.

Running Dijkstra's algorithm on a simple graph

As an example, we will use the following undirected weighted graph:

We are looking for the...