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Graph Machine Learning

You're reading from  Graph Machine Learning

Product type Book
Published in Jun 2021
Publisher Packt
ISBN-13 9781800204492
Pages 338 pages
Edition 1st Edition
Languages
Authors (3):
Claudio Stamile Claudio Stamile
Profile icon Claudio Stamile
Aldo Marzullo Aldo Marzullo
Profile icon Aldo Marzullo
Enrico Deusebio Enrico Deusebio
Profile icon Enrico Deusebio
View More author details

Table of Contents (15) Chapters

Preface 1. Section 1 – Introduction to Graph Machine Learning
2. Chapter 1: Getting Started with Graphs 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

Providing a quick overview of a dataset

To show you how to process a corpus of documents with the aim of extracting relevant information, we will be using a dataset derived from a well-known benchmark in the field of NLP: the so-called Reuters-21578. The original dataset includes a set of 21,578 news articles that were published in the financial Reuters newswire in 1987, which were assembled and indexed in categories. The original dataset has a very skewed distribution, with some categories appearing only in the training set or in the test set. For this reason, we will use a modified version, known as ApteMod, also referred to as Reuters-21578 Distribution 1.0, that has a smaller skew distribution and consistent labels between the training and test datasets.

Even though these articles are a bit outdated, the dataset has been used in a plethora of papers on NLP and still represents a dataset that's often used for benchmarking algorithms.

Indeed, Reuters-21578 contains enough...

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