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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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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

State-of-the-art graph algorithms

Published papers about graphs can be found in dedicated journals such as the Journal of Graph Algorithms and Applications (http://jgaa.info). Papers with code also do amazing work collecting papers where the code is publicly available. The graph section (https://paperswithcode.com/area/graphs) provides a nice overview of the top current research topics regarding graphs.

However, if you can't afford to read multiple papers a week, you can still extend your knowledge about graphs and stay up to date with the latest advances by regularly checking packages dedicated to graphs. The Neo4j Graph Data Science plugin is an example of such a package.

When your graph is stored in Neo4j, the GDS is very important and already provides many interesting algorithms. However, not all of them are implemented and some applications, such as graph embedding or overlapping community detection, may require other types of algorithms. To get an overview of the existing...

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