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Hands-On Graph Analytics with Neo4j

You're reading from   Hands-On Graph Analytics with Neo4j Perform graph processing and visualization techniques using connected data across your enterprise

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781839212611
Length 510 pages
Edition 1st Edition
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Author (1):
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 Scifo Scifo
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Scifo
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Graph Modeling with Neo4j
2. Graph Databases FREE CHAPTER 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

Importing data

So, after installing APOC and copying the data file into your import folder, you can simply call the apoc.import.graphml procedure in this way:

CALL apoc.import.graphml("manhattan_road_network.graphml", {defaultRelationshipType:"LINKED_TO"})

After a couple of seconds, you will see a result similar to this one:

4,426 nodes (junctions) were inserted and 9,626 relationships of type LINKED_TO representing road segments were created between them.

In order to facilitate the queries in the rest of this chapter, we will assign a label, Junction, to the newly created nodes:

MATCH (n) 
WHERE n.latitude IS NOT NULL AND n.longitude IS NOT NULL
SET n:Junction

Our graph is well imported. You can check a few nodes and relationships. For instance, those associated with Fifth Avenue look like the following diagram:

In the final section of this chapter, we will learn how to represent this data on a map for a more realistic visualization. Before that, let&apos...

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