Liberating Knowledge: Machine Learning Techniques with Neo4j
By Jocelyn Hoppa
July 3, 2019|Reading time: 13 minutes
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 →
Explore: ai • Connected Data • Graph Analytics • graph-based search • graphconnect • Hume • Knowledge Graph • machine learning • natural language understanding • neo4j
Neo4j Bloom 1.1: Simple, Powerful & Team Ready [Release]
By Bryce Merkl Sasaki
June 6, 2019|Reading time: 3 minutes
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.
Explore: Connected Data • cypher • Data Visualization • dba • Graph Analytics • graph database • graph traversals • graph visualization • Neo4j Bloom • Neo4j Desktop
15 Years Loving Graphs: Big Congrats & Thanks to Our Italian Partner LARUS
By Michael Hunger, Developer Relations
May 24, 2019|Reading time: 4 minutes
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 →
Explore: APOC • etl • Graph Analytics • Kafka • Larus • machine learning • Neo4j ETL • Neo4j Kafka integration • Neo4j Labs • Neo4j partner
Transforming the Enterprise: AI at Scale with Neo4j
By Jocelyn Hoppa
April 24, 2019|Reading time: 18 minutes
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.
Explore: AI at scale • customer 360 • enterprise AI • fraud detection • Graph Analytics • graph database • graph learning • graph recommendation engine • graphconnect • machine learning
Free O’Reilly Book: Graph Algorithms in Apache Spark and Neo4j
By Jocelyn Hoppa
April 15, 2019|Reading time: 3 minutes
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.
Explore: Connected Data • data scientists • developers • graph algorithms • Graph Analytics • intelligent solutions • machine learning • neo4j • oreilly • predictive analytics • spark
Graph Algorithms in Neo4j: Graph Algorithms in Practice
By Jocelyn Hoppa
April 8, 2019|Reading time: 5 minutes
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 →
Explore: APOC • cypher • graph algorithms • Graph Analytics • graph model • importing data • neo4j • PageRank • real-time recommendations • yelp
Graph Algorithms in Neo4j: Triangle Count & Clustering Coefficient
By Jocelyn Hoppa
March 25, 2019|Reading time: 4 minutes
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 →
Explore: Clustering Coefficient • community detection algorithms • cypher • global clustering • graph algorithms • Graph Analytics • intelligent solutions • local clustering • Louvain Modularity • Triangle Count
#GraphCast: Graph Analytics For The Throne [GoT]
By Bryce Merkl Sasaki
March 24, 2019|Reading time: 2 minutes
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 →
Explore: For The Throne • Game of Thrones • GoT • graph algorithms • Graph Analytics • GraphCast • Neo4j Online Meetup
Announcing Neo4j Labs: Incubating the Next Generation of Graph Developer Tooling
By Jocelyn Hoppa
March 21, 2019|Reading time: 2 minutes
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 →
Explore: APOC library • data integration • Docker integration • GRANDstack • graph algorithms • Graph Analytics • GraphQL • indexing procedures • Neo4j Graph Platform • Neo4j Labs
Graph Algorithms in Neo4j: Louvain Modularity
By Jocelyn Hoppa
March 18, 2019|Reading time: 4 minutes
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 →
Explore: community detection algorithms • cypher • detecting communities • fraud analytics • graph algorithms • Graph Analytics • intelligent solutions • Louvain Modularity • neo4j • Social Networks
Graph Algorithms in Neo4j: Label Propagation
By Jocelyn Hoppa
March 4, 2019|Reading time: 4 minutes
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 →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • graph database • Knowledge Graph • label propagation • large-scale networks • neo4j
Graph Algorithms in Neo4j: Weakly Connected Components
By Jocelyn Hoppa
February 25, 2019|Reading time: 3 minutes
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 →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • intelligent solutions • Master Data Management • union-find • Weakly Connected Components
Graph Algorithms in Neo4j: Strongly Connected Components
By Jocelyn Hoppa
February 18, 2019|Reading time: 3 minutes
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 →
Explore: community detection algorithms • Connected Data • cypher • graph algorithms • Graph Analytics • Graph Databases • intelligent solutions • Strongly Connected Components
Apache Spark Developers Have Voted to Include Cypher in Spark 3.0 [Update]
By Bryce Merkl Sasaki
February 15, 2019|Reading time: 4 minutes
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 →
Explore: apache spark • cypher • data integration • data science • graph algorithms • Graph Analytics • graph query language • Oracle • RDF • W3C
Graph Algorithms in Neo4j: Closeness Centrality
By Jocelyn Hoppa
February 11, 2019|Reading time: 4 minutes
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 →
Explore: centrality algorithms • closeness centrality • cypher • graph algorithms • Graph Analytics • graph database • Graph Search • intelligent solutions • neo4j • shortest paths
Graph Algorithms in Neo4j: Betweenness Centrality
By Jocelyn Hoppa
February 4, 2019|Reading time: 5 minutes
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 →
Explore: betweenness centrality • centrality algorithms • cypher • Genomics • graph algorithms • Graph Analytics • Graph Search • shortest paths
Get Control of Today’s Financial Regulations Using the Neo4j Risk Management Platform [Infographic]
By Jocelyn Hoppa
January 31, 2019|Reading time: 1 minute
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 →
Explore: financial regulations • Graph Analytics • graph database • graph technology • neo4j • risk compliance • risk management • risk management platform • risk reporting • siloed data
Graph Algorithms in Neo4j: Degree Centrality
By Jocelyn Hoppa
January 28, 2019|Reading time: 3 minutes
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 →
Explore: centrality algorithms • cypher • Degree Centrality • graph algorithms • Graph Analytics • graph database • Graph Search • PageRank • pathfinding • social network
Graph Algorithms in Neo4j: PageRank
By Jocelyn Hoppa
January 22, 2019|Reading time: 4 minutes
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 →
Explore: centrality algorithms • cypher • graph algorithms • Graph Analytics • graph search algorithms • Larry Page • machine learning • PageRank • Twitter analytics
Graph Algorithms in Neo4j: Minimum Weight Spanning Tree
By Jocelyn Hoppa
January 14, 2019|Reading time: 4 minutes
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 →
Explore: cypher • graph algorithms • Graph Analytics • graph database • Graph Search • Minimum Weight Spanning Tree • neo4j • pathfinding • telecom
Graph Algorithms in Neo4j: All Pairs Shortest Path
By Jocelyn Hoppa
January 7, 2019|Reading time: 3 minutes
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 →
Explore: All Pairs Shortest Path • call routing • cypher • disease spread • graph algorithms • Graph Analytics • Graph Search • neo4j • network failure • pathfinding
Announcing the Neo4j GraphTour in 8+ Cities Worldwide
By Bryce Merkl Sasaki
December 19, 2018|Reading time: 3 minutes
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 →
Explore: Connected Data • cypher • data integration • Graph Analytics • graph database • graph technology • graphconnect • GraphTour • neo4j • Neo4j Community
Graph Algorithms in Neo4j: Single Source Shortest Path
By Jocelyn Hoppa
December 17, 2018|Reading time: 3 minutes
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 →
Explore: cypher • Dijkstra's algorithm • graph algorithms • Graph Analytics • Graph Search • Open Shortest Path First • pathfinding • shortest path • Single Source Shortest Path • telecom
Graph Algorithms in Neo4j: Shortest Path
By Jocelyn Hoppa
December 10, 2018|Reading time: 4 minutes
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 →
Explore: cypher • Dijkstra's algorithm • Google Maps • graph algorithms • Graph Analytics • Graph Search • pathfinding • shortest path • Social Networks • web mapping tools
Graph Algorithms in Neo4j: The Neo4j Graph Algorithms Library
By Jocelyn Hoppa
December 3, 2018|Reading time: 4 minutes
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 →
Explore: Big Data • Connected Data • cypher • data valence • graph algorithms • graph analysis • Graph Analytics • graph database • Network Science • statistical analysis