Book Image

Learning Neo4j 3.x - Second Edition

By : Jerome Baton
Book Image

Learning Neo4j 3.x - Second Edition

By: Jerome Baton

Overview of this book

Neo4j is a graph database that allows traversing huge amounts of data with ease. This book aims at quickly getting you started with the popular graph database Neo4j. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases along with data modeling techniques for graph databases. You'll gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. Furthermore, you'll also learn to create awesome procedures using APOC and extend Neo4j's functionality, enabling integration, algorithmic analysis, and other advanced spatial operation capabilities on data. Through the course of the book you will come across implementation examples on the latest updates in Neo4j, such as in-graph indexes, scaling, performance improvements, visualization, data refactoring techniques, security enhancements, and much more. By the end of the book, you'll have gained the skills to design and implement modern spatial applications, from graphing data to unraveling business capabilities with the help of real-world use cases.
Table of Contents (24 chapters)
Title Page
Credits
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Social networking systems


Obviously, there are a lot of recommender systems that will be very specific to a domain. In the past couple of years, with the massive rise of social networking tools and social apps all around us, the interest in social recommender systems has grown massively. Essentially, we are looking to make useful new connections between people that are effectively part of the same social circle, but may not have realized it yet.

Looking at the following sample network should clarify this immediately:

A social networking graph

In the preceding simple network, there is a very high likelihood that we can close some friendship loops very easily, by suggesting connections between new links between people. Very often, we will be using the graph theory principle of triadic closures, meaning that we will be closing the missing links of the triangles in the structure of our network.

So let's explore this social networking use case some more in the following chapter with a very specific...