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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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Estelle Scifo Estelle Scifo
Author Profile Icon Estelle Scifo
Estelle 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
Spatial Data

Spatial data refers to anything that needs to be localized on the Earth. From points to localize a person or a point of interest on the Earth surface, to lines to model a street or a river path, and to areas to delimit countries and buildings, all of these geometries are spatial data. They have been harmonized within Geographic Information System (GIS), which provides a unified approach for representing these objects. In this chapter, we will discover the shapefile and GeoJSON formats. The full power of these systems is their ability to compute metrics based on these geometries with ease: getting a line length, a surface area, or computing the distance between objects.

While spatial data has always been important in the field of cartography, it has attracted more and more interest with the development of smartphones that are equipped with GPS sensors and are able...

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