This Week in Neo4j: ML on Graphs, Extraction Pipelines, Kubernetes, Cybersecurity, Knowledge Graph, and More Copy

There’s a wealth of fine content and varied perspectives on graphs in this week’s newsletter. The not-to-miss articles include transferring unstructured text – including emails, news articles, and more – into a knowledge graph. We also show you how to use Neo4j to analyze data for your ML project.

Keep reading for a discussion about the uses of graph databases in cybersecurity, and don’t miss the piece on Kubernetes deployment with the Neo4j Helm chart. We also test the ability of knowledge graphs to represent domains of knowledge, exploring how a graph encompassing multiple domains is used for discovering COVID-19 treatments.

Enjoy the graphy goodness!

Yolande Poirier

Elena is a specialist in Digital Engineering with RLE International, a leading engineering service provider for the automotive industry. She is also a very active Ninja and is currently seeking feedback on a new descriptor framework for a Neo4j database written by her colleague Jens Deininger. Reach out to her on LinkedIn.
FROM TEXT TO A KNOWLEDGE GRAPH: The Information Extraction Pipeline
The information to incorporate into knowledge graphs is often unstructured text, such as news articles, emails and scientific journal entries. Tomaz Bratanic shares how to build an information extraction pipeline to transform unstructured text inputs into a useful knowledge graph.
GRAPH DATA SCIENCE:  Demonstrating ML on Graphs
Dimitris Panagopoulos demonstrates how to use Neo4j and Python to analyze a sample of arXiv articles. The sample consists of 600 articles on mathematics from arXiv, an open-access archive of scholarly articles. He shares all the Python code in GitHub.
OPEN SECURITY SUMMIT: Using Neo4j for Cybersecurity

Dinis Cruz, David Fauth, Dave Voutila, and Irene Michlin discuss innovative use cases for graph databases with a special focus on Neo4j.

DATABASE: Be Awesome With Neo4j Graph Database in Kubernetes
Jon Owings explains how the Neo4j Helm chart helps run the Community or Enterprise Editions in your K8s deployment. He also uses Portworx and Pure Storage FlashArray in his example.
KNOWLEDGE GRAPH: Is a Knowledge Graph Capable of Capturing Human Knowledge?
Alessandro Negro demonstrates how knowledge graphs are capable of representing knowledge in multiple domains. He shows how machine learning algorithms can be properly fed by graphs.
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Neo4j Live: Discover Neo4j AuraDB Free with Michael and Adam is on April 4.

Going Meta – Ep 3: Controlling the shape of your graph with SHACL is on April 5.

Don’t miss the weekly videos in the Bite-Sized Neo4j for Data Scientists series. In parts 25 to 29, Clair Sullivan presents a five-part series to help with your Kaggle competition graph.