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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
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Authors (2):
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Jerome Baton Jerome Baton
Author Profile Icon Jerome Baton
Jerome Baton
Rik Van Bruggen Rik Van Bruggen
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Rik Van Bruggen
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Toc

Table of Contents (17) Chapters Close

Preface 1. Graph Theory and Databases 2. Getting Started with Neo4j FREE CHAPTER 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

Questions and answers

Q1: In order to build a recommendation system, I need an artificial intelligence engine that will take a look at my data and discover the recommendation patterns for me automatically.

  1. True
  2. False

Answer: False. Recommender systems can be based on business knowledge that your staff already has, a visual pattern you discover while browsing the data, or some kind of algorithmic machine learning process. All three can provide meaningful recommendation patterns for your business applications.

Q2: Recommender systems can only be applied in an Amazon-style retail environment, where you have a massive amount of data to base your recommendations on.

  1. True
  2. False

Answer: False. Recommendations are useful in many different business domains, not just retail product recommendations. Fraud detection systems (I recommend that you put this person in jail.) are just one...

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