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Graph Machine Learning

You're reading from   Graph Machine Learning Take graph data to the next level by applying machine learning techniques and algorithms

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Product type Paperback
Published in Jun 2021
Publisher Packt
ISBN-13 9781800204492
Length 338 pages
Edition 1st Edition
Languages
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Authors (3):
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Aldo Marzullo Aldo Marzullo
Author Profile Icon Aldo Marzullo
Aldo Marzullo
Claudio Stamile Claudio Stamile
Author Profile Icon Claudio Stamile
Claudio Stamile
Enrico Deusebio Enrico Deusebio
Author Profile Icon Enrico Deusebio
Enrico Deusebio
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1 – Introduction to Graph Machine Learning
2. Chapter 1: Getting Started with Graphs FREE CHAPTER 3. Chapter 2: Graph Machine Learning 4. Section 2 – Machine Learning on Graphs
5. Chapter 3: Unsupervised Graph Learning 6. Chapter 4: Supervised Graph Learning 7. Chapter 5: Problems with Machine Learning on Graphs 8. Section 3 – Advanced Applications of Graph Machine Learning
9. Chapter 6: Social Network Graphs 10. Chapter 7: Text Analytics and Natural Language Processing Using Graphs 11. Chapter 8:Graph Analysis for Credit Card Transactions 12. Chapter 9: Building a Data-Driven Graph-Powered Application 13. Chapter 10: Novel Trends on Graphs 14. Other Books You May Enjoy

Chapter 8:Graph Analysis for Credit Card Transactions

Analysis of financial data is one of the most common and important domains in big data and data analysis. Indeed, due to the increasing number of mobile devices and the introduction of a standard platform for online payment, the amount of transactional data that banks are producing and consuming is increasing exponentially.

As a consequence, new tools and techniques are needed to exploit as much as we can from this huge amount of information in order to better understand customers' behavior and support data-driven decisions in business processes. Data can also be used to build better mechanisms to improve security in the online payment process. Indeed, as online payment systems are becoming increasingly popular due to e-commerce platforms, at the same time, cases of fraud are also increasing. An example of a fraudulent transaction is a transaction performed with a stolen credit card. Indeed, in this case, the fraudulent...

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