This Week in Neo4j: Algorithms, GraphQL, Knowledge Graph Book, GraphStuff.FM Podcast, and More

Welcome to this week’s newsletter! Check out the blog on graph algorithms by Alison Cossette (Hot Algo Summer) with clearly explained examples and easy to follow code snippets. And there’s angrykoala’s end-to-end technical blog (Improving a Node.js GraphQL Server Performance) on identifying and fixing performance issues of the @neo4j/graphql library. Otherwise, you could listen to the latest episode of GraphStuff.FM, “What Is Graph Data Science?”

Yolande Poirier


Donovan is an Expert Software Engineer at JB Hunt, specializing in .Net and Java applications in and around Azure. He is actively working to automate processes, eliminate human errors while using graphs. In his NODES talk, he discusses IAC SchemaSmith for data governance at JB Hunt. Watch his talk!

ALGORITHMS: Hot Algo Summer
Alison Cossette demonstrates the use of 3 algorithms that are new to Graph Data Science 2.4 in the categories of community detection, pathfinding, and graph sampling. There are working code samples for experimenting with the algorithms K-Core Decomposition, Bellman-Ford Shortest-Path, and Common Neighbour Aware Random Walk.
TROUBLESHOOTING: Improving a Node.js GraphQL Server Performance
angrykoala discusses the tools and processes used to identify and fix some of the performance problems in a Node.js server for GraphQL. For users of the @neo4j/graphql library, these performance improvements are available in @neo4j/graphql 3.19.
LIVE STREAM: Graph-Based Linguistics

Maria Di Maro is a Post-Doc at the University of Naples ‘Federico II.’ In this talk, she emphasizes the potential of graphs to extract information more intricate and detailed than corpus linguistics and basic text-based statistical models.

A BOOK REVIEW: Knowledge Graphs

Sixing Huang summarizes many of the main points of “Knowledge Graphs”, by Jesús Barrasa and Jim Webber. In this short volume, the authors cover the key aspects, including the definition, construction, types, and the roles of knowledge graphs in contextual AI and business digital twins.

PODCAST: What Is Graph Data Science?

Listen to this episode where full-stack application developers and data scientists explore the complex world of data science from a graphy perspective. Join Jennifer Reif, William Lyon, Andreas Kollegger and Alison Cossette for a discussion on using knowledge graphs in data science and how the Graph Data Science library relates to the larger world of AI.

TWEET OF THE WEEK: @graph_aware

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