Graph Algorithms: Make Election Data Great Again

Editor’s Note: This presentation was given by John Swain at GraphConnect San Francisco in October 2016. Summary In this presentation, learn how John Swain of Right Relevance (and Microsoft Azure) set out to analyze Twitter conversations around both Brexit and… Learn More →

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The Emergence of the Enterprise DataFabric

Editor’s Note: This presentation was given by Mark Kvamme and Clark Richey at GraphConnect San Francisco in October 2016. Presentation Summary Enterprises are faced with a variety of challenges when it comes to managing data, largely due to the disparate… Learn More →

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How NASA Finds Critical Data through a Knowledge Graph

Editor’s Note: This presentation was given by David Meza at GraphConnect San Francisco in October 2016. Here’s a quick review of what he covered: What is a knowledge architecture? What are the benefits of a knowledge architecture? The power of… Learn More →

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The 5-Minute Interview: Daniel Himmelstein, Postdoctoral Fellow at University of Pennsylvania

“This is a really advanced graph algorithm and Cypher nailed it,” said Daniel Himmelstein, a Postdoctoral Fellow at the University of Pennsylvania. Before using Neo4j, it took as many as 1,000 lines of code to write the main query for… Learn More →

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Who Cares What Beyoncé Ate for Lunch?

Editor’s Note: This presentation was given by Alicia Powers at GraphConnect Europe in April 2016. Here’s a quick review of what she covered: The global obesity epidemic How to verify your data model The key components of a recommendation engine… Learn More →

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Building a Real-Time Recommendation Engine with Data Science

Editor’s Note: This presentation was given by Nicole White at GraphConnect Europe in April 2016. Here’s a quick review of what she covered: Basic graph-powered recommendations Social recommendations Similarity recommendations Cluster recommendations – What we’re going to be talking about… Learn More →

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Making a Difference: The Public Neo4j-Users Slack Group

We’ve been asked several time in the past to open a neo4j-users Slack group for the many enthusiastic people in the Neo4j user community. Now, that Slack group is a reality. This group is meant to be a hip alternative… Learn More →

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The Secret to More Efficient Data Science with Neo4j and R [OSCON Preview]

It’s a sad but true fact: Most data scientists spend 50-80% of their time cleaning and munging data and only a fraction of their time actually building predictive models. This is most often true in a traditional stack, where most… Learn More →

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