I was inspired by Insights from Visualizing Public Data on Twitch post. The author uses Gephi to perform graph analysis on the Twitch network and visualize the results. Twitch is an online platform that allows users to share their content via live stream. Twitch streamers broadcast their gameplay or activity by sharing their screen with fans who can hear and watch them live. I wondered what kind of analysis we could make if we used a graph database instead of Gephi to store the network information. This blog post will show you how to design and construct a knowledge graph…

NEuler is a graph data science playground application designed to help you execute and understand graph algorithms in Neo4j. With only a couple of clicks, you can import example data, execute various graph algorithms, and visualize their results. It is available as an extension to Neo4j Desktop, and you can also use it in combination with Neo4j Sandbox.

In this blog post, I will use the Movies sandbox project to demonstrate how to quickly visualize graph embedding results with a t-SNE scatter plot.

Setting Up the Neo4j Sandbox Environment

You can follow this link to automatically create a Movies sandbox project. If you choose to, you…

I am thrilled to present my latest project I have been working on. If you have been following my posts, you know that I am passionate about combining natural language processing and knowledge graphs. In this blog post, I will present my implementation of an information extraction data pipeline. Later on, I will also explain why I see the combination of NLP and graphs as one of the paths to explainable AI.

Information extraction pipeline

What exactly is an information extraction pipeline? To put it in simple terms, information extraction is the task of extracting structured information from unstructured data such as text.

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A wealth of information is being produced every day on the internet. Understanding the news and other content-generating websites is becoming increasingly crucial to successfully run a business. It can help you spot opportunities, generate new leads, or provide indicators about the economy.

In this blog post, I want to show you how you can create a news monitoring data pipeline that combines natural language processing (NLP) and knowledge graph technologies.

The data pipeline consists of three parts. In the first part, we scrape articles from an Internet provider of news. Next, we run the articles through an NLP pipeline…

The use of knowledge graphs and graph analytics pipeline is getting more and more popular. If you keep an eye on the graph analytics field, you already know that graph neural networks are trending. Unfortunately, there aren’t many tutorials out there on how to use them in a practical application. For this reason, I have decided to write this blog post, where you will learn how to train a convolutional graph neural network and integrate it into your machine learning workflow to improve downstream classification model accuracy.

Agenda

In this example, you will reproduce the protein role classification task from the…

In Europe, we are deep in the second wave of Covid lockdown. I’ve seen some motivational speakers talk about using this time and learning a new skillset. As a child, I’ve always liked nuclear experiments, so I decided to build a reactor in my basement and try some experiments. I’ve already got a basement, so now I only need to learn nuclear physics or maybe get some nuclear researchers to help me out.

I’ve got the idea from Estelle Scifo, who imported and analyzed the ArXiv dataset in Neo4j. We’ll take a detailed look at the nuclear experiments category of…

Hands-on Tutorials, Marvel network analysis

A wise man once said that the 2020–30 decade will be the decade of graph data science. Actually, that happened just a few days ago at the Nodes 2020 conference, and that wise man was Emil Eifrem presenting at the keynote of the Nodes 2020. In case you missed the conference, all the presentations are already available online.

Only fitting Emil’s statement, a pre-release of the 1.4 version of the Neo4j Graph Data Science library was published a couple of days ago. It is a significant milestone for the GDS library. A lot of new features were added in this…

Traveling tourist

In the first part of the series, we constructed a knowledge graph of monuments located in Spain from WikiData API. Now we’ll put on our graph data science goggles and explore various pathfinding algorithms available in the Neo4j Graph Data Science library. To top it off, we’ll look at a brute force solution for a Santa Claus problem. Now, you might wonder what a Santa Claus problem is. It is a variation of the traveling salesman problem, except we don’t require the solution to end in the same city as it started. …