What is it about?
Machine Learning is a widely used technology with a number of applications in technological, scientific, industrial and business domains. Complex networks are used the characterize interactions of people, products, social, business, scientific and technological applications. We show how to easily apply machine learning techniques in complex and social networks. We do so by highlighting key applications in centrality measures, which are key to understanding the spread of information in complex and social networks.
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Why is it important?
Using machine learning can be challenging in a number of applications. However, in order to make this use feasible, step by step guides are highly relevant. This paper provides an easy but founded introduction and guide on how to use machine learning techniques in a number of applications.
Perspectives
We hope this paper will serve as a working guide to both professionals and researchers alike. We avoided technicalities and focused on the application of machine learning, making the content easy to follow.
Luis Lamb
Universidade Federal do Rio Grande do Sul
Read the Original
This page is a summary of: Machine Learning in Network Centrality Measures, ACM Computing Surveys, October 2018, ACM (Association for Computing Machinery),
DOI: 10.1145/3237192.
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