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Learning Neo4j 3.x

You're reading from   Learning Neo4j 3.x Effective data modeling, performance tuning and data visualization techniques in Neo4j

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786466143
Length 316 pages
Edition 2nd Edition
Languages
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Authors (2):
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Jerome Baton Jerome Baton
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Jerome Baton
 Van Bruggen Van Bruggen
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Van Bruggen
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Toc

Table of Contents (24) Chapters Close

Title Page
Credits
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Graph Theory and Databases FREE CHAPTER 2. Getting Started with Neo4j 3. Modeling Data for Neo4j 4. Getting Started with Cypher 5. Awesome Procedures on Cypher - APOC 6. Extending Cypher 7. Query Performance Tuning 8. Importing Data into Neo4j 9. Going Spatial 10. Security 11. Visualizations for Neo4j 12. Data Refactoring with Neo4j 13. Clustering 14. Use Case Example - Recommendations 15. Use Case Example - Impact Analysis and Simulation 16. Tips and Tricks

Specific query examples for recommendations


In this example dataset, we will explore a couple of interesting queries that would allow us--with the information that is available to us--to construct interesting recommendations for our hypothetical users. We will do so along different axes:

  • Product purchases
  • Brand loyalty
  • Social and/or family ties

Let's start with the first and work our way through.

Recommendations based on product purchases

Let's build this thing from the ground up. The first query that we want to write is based on past purchasing behavior. We would like to find people that already share a couple of products that they have purchased in the past, but that also explicitly do not share a number of other products. In our data model, this Cypher query would go something as follows:

match (p1:Person)-[:BOUGHT]->(prod1:Product)<-[:BOUGHT]-(p2:Person)-[:BOUGHT]->(prod2:Product) 
where not(p1-[:BOUGHT]->prod2) 
return p1.name as FirstPerson, p2.name as SecondPerson, prod1.name...
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