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Learning Neo4j 3.x - Second Edition

You're reading from  Learning Neo4j 3.x - Second Edition

Product type Book
Published in Oct 2017
Publisher Packt
ISBN-13 9781786466143
Pages 316 pages
Edition 2nd Edition
Languages
Concepts
Author (1):
Jerome Baton Jerome Baton
Profile icon Jerome Baton

Table of Contents (24) Chapters

Title Page
Credits
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Graph Theory and Databases 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

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 example of a business application that has nothing to do with retail but that will use the same pattern matching capabilities...

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