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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

Nodes

In Neo4j, vertices are called nodes. Nodes can be of different types, like Question and Answer were in our former example. In order to differentiate those entities, nodes can have a label. If we continue the parallel with SQL, all nodes with a given label would be in the same table. But the analogy ends here, because nodes can have multiple labels. For instance, Clark Kent is a journalist, but he is also a superhero; the node representing this person can then have the two labels: Journalist and SuperHero.

Labels define the kind of entity the node belongs to. It is also important to store the characteristics of that entity. In Neo4j, this is done by attaching properties to nodes.

You have been reading a chapter from
Hands-On Graph Analytics with Neo4j
Published in: Aug 2020
Publisher: Packt
ISBN-13: 9781839212611
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