Liberating Knowledge: Machine Learning Techniques with Neo4j

Editor’s Note: This presentation was given by Rob Schley, Dr. Alessandro Negro and Christophe Willemsen at GraphConnect New York City in September 2018 Presentation Summary Following a brief philosophical background by Rob Schley, we dive into Hume’s core by exploring… Read more →

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Neo4j Bloom 1.1: Simple, Powerful & Team Ready [Release]

Discover what’s new in the 1.1 release of the Neo4j Bloom graph data visualization tool, including internet browser capabilities and new role-based security.

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15 Years Loving Graphs: Big Congrats & Thanks to Our Italian Partner LARUS

I just returned from Venice, where enjoyed not only the weather and food but …​ Had an amazing time in Venice, Italy to celebrate the 15th anniversary of our friends and partners from @AgileLARUS. Thanks a lot @inserpio for the… Read more →

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Transforming the Enterprise: AI at Scale with Neo4j

Discover how Ernst and Young takes advantage of graph-driven enterprise AI and machine learning to develop stronger fraud-detection and customer 360 mapping tools.

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Free O’Reilly Book: Graph Algorithms in Apache Spark and Neo4j

Grab your free copy of the brand new O’Reilly book, “Graph Algorithms: Practical Examples in Apache Spark & Neo4j” – a practical guide to graph analytics.

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Graph Algorithms in Neo4j: Graph Algorithms in Practice

Graph analytics have value only if you have the skills to use them and if they can quickly deliver the insights you need. This blog provides a hands-on example using Neo4j on data from Yelp’s Annual Dataset challenge. Graph algorithms… Read more →

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Graph Algorithms in Neo4j: Triangle Count & Clustering Coefficient

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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#GraphCast: Graph Analytics For The Throne [GoT]

Welcome to this week’s #GraphCast – our series featuring what you might have missed in Neo4j media from the past fortnight. Last time, I pointed out that we have an incredible Neo4j Online Meetup and that you’re a square if… Read more →

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Announcing Neo4j Labs: Incubating the Next Generation of Graph Developer Tooling

As the Director of the Developer Relations engineering team, I couldn’t be more proud of the things we have achieved over the last few years. Our focus was to build integrations, tools and libraries that extend the Neo4j Graph Platform… Read more →

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Graph Algorithms in Neo4j: Louvain Modularity

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Label Propagation

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Weakly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Strongly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Apache Spark Developers Have Voted to Include Cypher in Spark 3.0 [Update]

The community vote by Apache Spark contributors has just closed – and the results are positive. Thank you to everyone who participated when we asked for your votes and feedback. As part of the preparations for a forthcoming Apache Spark… Read more →

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Graph Algorithms in Neo4j: Closeness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Betweenness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Get Control of Today’s Financial Regulations Using the Neo4j Risk Management Platform [Infographic]

Financial regulations in the U.S. has become a complicated and fragmented system, but why? Various authorities creating compliance laws include a cast of six federal regulating agencies: The Federal Reserve, Office of the Comptroller of the Currency, the National Credit… Read more →

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Graph Algorithms in Neo4j: Degree Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: PageRank

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Minimum Weight Spanning Tree

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: All Pairs Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Announcing the Neo4j GraphTour in 8+ Cities Worldwide

Starting this February, Neo4j is coming to a city near you to deliver a full day of sessions on how graph database technology is revolutionizing the modern enterprise. The GraphTour Basics This one-day local event will teach you all you… Read more →

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Graph Algorithms in Neo4j: Single Source Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: The Neo4j Graph Algorithms Library

The Neo4j Graph Algorithms Library is used on your connected data to gain new insights more easily within Neo4j. These graph algorithms improve results from your graph data, for example by focusing on particular communities or favoring popular entities. This… Read more →

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