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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

Querying Wikidata

All the queries we are going to write here can be tested using the online Wikidata tool at https://query.wikidata.org/.

If you have done the assessments at the end of Chapter 2, Cypher Query Language, your GitHub graph must have nodes with label Location, containing the city each user is declared to live in. If you skipped Chapter 2 or the assessment, you can find this graph in the GitHub repository for this chapter. The current graph schema is the following:

Our goal will be to assign a country to each of the locations. Let's start from the most frequent location within Neo4j contributors, Malmö. This is a city in Sweden where the company building and maintaining Neo4j, Neo Inc., has its main offices.

How can we find the country in which Malmö is located using Wikidata? We first need to find the page regarding Malmö on Wikidata. A simple search on your favorite search engine should lead you to https://www.wikidata.org/wiki/Q2211. ...

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