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Graph Data Modeling in Python

You're reading from   Graph Data Modeling in Python A practical guide to curating, analyzing, and modeling data with graphs

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618035
Length 236 pages
Edition 1st Edition
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Authors (2):
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Gary Hutson Gary Hutson
Author Profile Icon Gary Hutson
Gary Hutson
Matt Jackson Matt Jackson
Author Profile Icon Matt Jackson
Matt Jackson
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Getting Started with Graph Data Modeling
2. Chapter 1: Introducing Graphs in the Real World FREE CHAPTER 3. Chapter 2: Working with Graph Data Models 4. Part 2: Making the Graph Transition
5. Chapter 3: Data Model Transformation – Relational to Graph Databases 6. Chapter 4: Building a Knowledge Graph 7. Part 3: Storing and Productionizing Graphs
8. Chapter 5: Working with Graph Databases 9. Chapter 6: Pipeline Development 10. Chapter 7: Refactoring and Evolving Schemas 11. Part 4: Graphing Like a Pro
12. Chapter 8: Perfect Projections 13. Chapter 9: Common Errors and Debugging 14. Index 15. Other Books You May Enjoy

Part 2: Making the Graph Transition

Armed with what we learned from the previous part around the fundamentals, we can now move on to explain how and why graph databases are different to traditional relational database structures, and how and why you would want to use them. We will be working in MySQL and Python in the data model transformation chapter, which will culminate in building a recommendation engine to recommend a game to a user.

Once we have that chapter in our arsenal, we will move on to delve into how we can build a knowledge graph. This will involve getting our hands dirty with some data ingestion and cleaning, before we then create our knowledge graph and perform community detection over the top, to find medical abstracts that relate to a specific subject, as community detection’s role is to find similar communities in entities, or in this sense, similar research based on a specific abstract text and what terms are mentioned in the text.

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