This Week in Neo4j: Cluster Analysis, Entity Resolution, Cloud Integrations, Docker, and More

Welcome to this week’s newsletter! Take a trip on an ML pipeline and check out Matthew Filbert’s blog, Entity Resolution in Reagent. How his team arrived at specific problem modeling and algorithms are interesting topics as is the pipeline walkthrough, from selection of ML type and data preprocessing to training the model and making predictions.

Also recommend Artem Ryasik’s blog, ArtGraph Cluster Analysis, for its detailed explanations of knowledge graph analytics and use of clustering algorithms.

Yolande Poirier


Ajmal Aziz is a Senior Solutions Engineer at Databricks. Prior to joining Databricks, he was at the University of Cambridge researching Graph Neural Networks. He spends most of his weekends combining his passions for distributed data processing and machine learning. Connect with him on LinkedIn

In his NODES 2022 presentation, Neo4j and Databricks demonstrate a reference architecture that leverages each other’s strengths in connected data and big data to ingest, transform, analyse, and present insights. Watch his talk!

KNOWLEDGE GRAPH: ArtGraph Cluster Analysis
Artem Ryasik departs from his previous graph analysis theme of a biomedical graph, to consider a graph of artists and their works. ArtGraph was developed to classify style and genre using a combination the image itself with the context of the artwork and its creator.
INTERVIEW: Understanding Graph Databases With Neo4j
Watch this video interview to see a clear presentation of Neo4j technology, customer use cases, and integration with Google Cloud. Ben Lackey, Neo4j Cloud Partner Architecture Team, is interviewed by Debi Cabrera, Developer Advocate at Google.
TUTORIAL: Exploring Graph Database With Neo4j DB and Docker Desktop

Get an instance of Neo4j running in a container on your local machine in this livestream tutorial with Abhishek Das. After installation of the Neo4j Docker extension, he covers the basics of graph technology and dives into querying with Cypher for the second half hour.

TOOL: Entity Resolution in Reagent

Margin Research’s Matthew Filbert explains how Social Cyber extracts meaningful information from the social network of open source software developers. Their Reagent tool is hosted on a graph database, and LLMs and AI/ML pipelines complete its architecture.

INTRODUCTION: Graph Data Science

Yogesh Kulkarni outlines Neo4j and Graph Data Science at Google Cloud Community Day 2023 in Pune, India. Yogesh holds a PhD in Geometric Modeling and is a  Google Developer Expert in machine learning as well as being a top writer on Medium.


Don’t forget to share it if you like it!