This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more

Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases!
Last week, we celebrated the publication of ISO GQL and we announced the Call for Papers for NODES 2024. I couldn’t even feature the latter one in last week’s edition, so we will take a proper look at that this week.
Additionally, we have Data Modelling for RAG Applications, Neo4j Event Calendar and creating Knowledge Graphs from Crime data.

I added a few more links for Graph Database Beginners, including how to learn using aggregates with Cypher.

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I hope you enjoy this issue,
Alexander Erdl



Michal has experience with multiple programming languages and has worked in different IT areas, such as software development, web development, game development, and XR.
Connect with him on LinkedIn.

In a recent livestream “CypherGUI – User-Friendly Administration for Neo4j” we looked at his latest user-friendly GUI administration tool for graph databases. It is usable without knowledge of cypher query language.

Michal Štefaňák
NODES 2024: Call for Papers is open
NODES, the premier developer conference dedicated to graph-powered applications and contextual AI, returns for its sixth year on November 7, 2024. Yolande Poirier summarises the most important bits in this blog post. The Call for Papers is open and we invite you to submit your stories!
DATA MODELLING: Graph Data Models for RAG Applications
When building a retrieval augmented generation (RAG) application, it can be tempting to dump your documents in either a vector or graph database, generate some embeddings, and start running cosine similarity. In this article by Alex Gilmore, you get to see a few alternative graph data models that can be used to enhance these applications and the unique benefits each model provides.
EVENTS: Neo4j on Lu.Ma
We have a Neo4j calendar on Lu.Ma, where you can find our upcoming Meetups and livestream in one place. Subscribe to the calendar to get notifications – so you don’t miss the next graph event happening in your region.
KNOWLEDGE GRAPH: Extraction of unstructured data to generate crime knowledge graphs: Past, Present & Future
An interdisciplinary research study combining generative AI, NLP – natural language processing, criminology, and graph database. In this article, Deepa Venkatraman summarises what has been presented in a talk at NODES 2023.

TWEET OF THE WEEK: Philip Rathle

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