Neo4j Graph Data Science has just unleashed a collection of innovative algorithms that can solve some of your pain. Check them out! Read more →
Fast-track your graph database setup with a preloaded Neo4j: PubChem, NCI60, ChEMBL datasets. Explore chemical compounds and biomedical experiments effortlessly. Read more →
Hands-On Workshop Exploring Working With Road Network Data and Routing With Graph AlgorithmsRunning path-finding algorithms on large datasets is a use case that graph databases are particularly well suited for. While often pathfinding algorithms are used for finding routes using… Read more →
ChatGPT has changed how I, and probably most of you, look at AI and chatbots. We can use chatbots to help us find information, construct creative works, and more.However, one problem with ChatGPT and similar chatbots is that they can hallucinate… Read more →
Discover how Neo4j supports cross-disciplinary research between technology and humanities researches in conversational AI. Read more →
NODES 2022 is a free, multi-track, two-day virtual conference of highly technical presentations by developers and data scientists solving problems with graphs. Read more →
Knowing your users is vital to any business. When your users can interact with each other on a social media platform, content sharing platform, or even work-related platforms, you can construct a network between your users based on their interactions and extract graph-based features to segment your users. Of course, these same approaches can be applied to other platforms that are not user-centric. Read more →
A wave of graph-based approaches to data science and machine learning is rising. We live in an era where the exponential growth of graph technology is predicted [1]. The ability to analyze data points through the context of their relationships… Read more →
Learn the basic syntax of the newly released Python client for Neo4j Graph Data Science and how to get started. Read more →
In this blog post, we’ll use Neo4j to turn the European Gas Network into a knowledge graph to analyze the data.Photo by Rostislav Artov, UnsplashThe crisis between Ukraine and Russia caused relations between Russia and the E.U. to fall to the lowest… Read more →
In part 4 of our fraud detection series, we will cover how to apply graph machine learning to predict the high fraud risk user accounts we labeled in parts 1, 2, and 3. Read more →
In part 3 of our fraud detection series, we may want to expand beyond our business logic to automatically identify other users that are suspiciously similar to the fraud risks already identified. Read more →
In part 2 of this fraud detection series, we will provide more formal definitions for resolving entities that will allow us to partition well-defined communities in a scalable manner. Read more →
In the first part of this fraud detection series, we will introduce the sample graph dataset we are using and begin exploring the graph for potential fraud patterns. Read more →
Fraud Detection is one of today's most challenging data science problems. Thankfully, Neo4j Graph Data Science (GDS) offers practical solutions that empower data scientists to make rapid progress in fraud detection analytics and machine learning. Read more →
In this post we explore how to get started with practical and scalable recommendation in graph. We will walk through a fundamental example with news recommendation on a dataset containing 17.5 million click events and around 750K users. Read more →
Check out how to analyze Twitch streamers and their audiences in Sandbox with Neo4j APOC and Graph Data Science. Read more →
Learn how you can use correlation between stock prices to infer a similarity network between stocks – and then use that network information to help you diversify your portfolio. Read more →
Check out the newest algorithm in the GDS Library, Approximate Maximum K-cut, to cluster related products and separate conflicting entities. Read more →
Register for a week of live, hands-on training, from writing your first graph database query to using ML to build a knowledge graph. Read more →
In this post, I’d like to go over a number of the key changes from the past two versions of Bloom, and discuss how they might be helpful to analysts and data scientists, as well as developers involved in these specialties. Read more →
We’re bucking the recent trend of pre-recorded talks with a fully immersive, fully interactive experience for NODES 2021. Tell your colleagues to leave you alone that day, because you will not want to miss out! Read more →
APOC contains about 500 procedures and functions, here we’ll discuss some of them that are very interesting and use cases about their applications. Enjoy!Started as a very simple collection of useful Procedures and Functions in 2016 the APOC project raised… Read more →
In this episode of the GraphStuff.FM podcast, Lju Lazarevic and Will Lyon break down how the different pieces of the Neo4j Graph Data Platform fit together. Read more →
On April 15 every year, the global graph community gets together to celebrate the evolution of the graph ecosystem by marking the birthday of the creator of graph theory, Leonhard Euler. This year the community gathered virtually during a special extended live stream to mark the occasion. Read more →