(testing signal)

Tag: GraphAnalysis

Keyphrase Extraction with Graph Centrality

Taking advantage of graph representations to extract relevant phrases from free-textFree-text lacks explicit structure and standardisation. In this post we saw how to represent free-text with a graph, making its structure explicit and easily manageable by downstream algorithms.In this post, I will show you how to solve the task of Keyphrase Extraction using a graph representation of free-text. As the name suggests, the objective of the task is to return a list of relevant phrases (one or…

Machine Learning on Graphs, Part 1

Photo by Alina Grubnyak on Unsplash

Collecting basic statistics

In a series of posts, I will provide an overview of several machine learning approaches to learning from graph data. Starting with basic statistics that are used to describe graphs, I will go deeper into the subject by discussing node embeddings, graph kernels, graph signal processing, and eventually graph neural networks. The posts are intended to reflect on my personal experience in academia and industry, including some of my research papers. My main motivation is to present first some basic approaches to machine learning on graphs that should be used before digging into advanced algorithms like graph neural networks.

In the first post, I present some common techniques for graph analysis that should help us better understand our data.… Read more...