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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

Other applications of centrality algorithms

Beyond fraud detection, centrality algorithms can also be used in many contexts. We have already talked about influencer detection in a social network. By now, you may understand why PageRank is a good choice in that case since it not only takes into account a given person's connections, but also the connections of those connections... In this case, overall, the information spread will be faster if it starts from a node with a higher PageRank.

Biology and genetics are two other important fields of application of centrality. For instance, when building a network of protein interactions inside some yeast, researchers can determine which of these proteins are more essential to the yeast and which are not vital. Many other applications of centrality, especially PageRank, have been explored in the domain of genetics to determine gene importance in some given disease, for instance. See the article PageRank beyond the web (link in the Further...

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