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Hands-On Graph Analytics with Neo4j

You're reading from  Hands-On Graph Analytics with Neo4j

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781839212611
Pages 510 pages
Edition 1st Edition
Languages
Author (1):
Estelle Scifo Estelle Scifo
Profile icon Estelle Scifo
Toc

Table of Contents (18) Chapters close

Preface 1. Section 1: Graph Modeling with Neo4j
2. Graph Databases 3. The Cypher Query Language 4. Empowering Your Business with Pure Cypher 5. Section 2: Graph Algorithms
6. The Graph Data Science Library and Path Finding 7. Spatial Data 8. Node Importance 9. Community Detection and Similarity Measures 10. Section 3: Machine Learning on Graphs
11. Using Graph-based Features in Machine Learning 12. Predicting Relationships 13. Graph Embedding - from Graphs to Matrices 14. Section 4: Neo4j for Production
15. Using Neo4j in Your Web Application 16. Neo4j at Scale 17. Other Books You May Enjoy

Questions

In order to test your understanding, try to answer the following questions. The answers are provided in the Assessment part at the end of this book:

  1. The GDS plugin and projected graphs:
  • Why does the GDS plugin use projected graphs?
  • Where are these projected graphs stored?
  • What are the differences between named and anonymous projected graphs?
  • Create a projected graph containing:
  • Nodes: label Node
  • Relationships: types REL1 and REL2
  • Create a projected graph with:
  • Nodes: labels Node1 and Node2
  • Relationships: type REL1 and properties prop1 and prop2
  • How do you consume the results of a graph algorithm from the GDS plugin?
  1. Pathfinding:
  • Which algorithms are based on Dijkstra's algorithm?
  • What is the important restriction regarding an edge's weight for these algorithms?
  • What information is needed to use the A* algorithm?
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