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
Large-Scale Real-Time Recommendations with Neo4j
By Jocelyn Hoppa
January 30, 2019|Reading time: 7 minutes
Editor’s Note: This presentation was given by Tim Hanssen at GraphConnect 2018 in New York City. Presentation Summary Prepr is a multi-channel engagement platform that streamlines content workflows and powers valuable audience interactions. They were using the MySQL relational database… Read more →
Explore: cypher • dynamic queue • engagement platform • event recommendations • graphconnect • MySQL • native graph database • real-time recommendations • relational database
This Week in Neo4j – Anti-Money Laundering Investigation, Replicating The GitHub GraphQL API, Getting Started with machine learning on graphs
By Mark Needham
January 5, 2019|Reading time: 3 minutes
Happy New Year everybody, and welcome to our first version of TWIN4j of 2019. I’d only just got used to writing the year as 2018! This is traditionally a quiet week, but we’ve still got some good stuff for you… Read more →
Explore: anti-money laundering • DeepMind • github • GraphQL • machine learning • Neo4j Community • real-time recommendations • twin4j
How Real-Time Recommendations Increase Revenues, Optimize Margins and Delight Customers [Infographic]
By Jocelyn Hoppa
November 8, 2018|Reading time: 1 minute
“You may also like” sounds simple, but there’s a lot happening behind the scenes. Real-time recommendations work best when they take into account both the user’s needs (what is of interest to them) and your business strategy (items you need… Read more →
Explore: business rules • collaborative filtering • financial services • government services • graph platform • graph technology • Healthcare • knowledge-based filtering • neo4j • real-time recommendations
Graph Algorithms in Neo4j: Use Cases for Graph Transactions & Analytics
By Jocelyn Hoppa
November 5, 2018|Reading time: 4 minutes
Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions. This blog series is designed to help you better leverage graph analytics so you can effectively innovate… Read more →
Explore: ai • customer 360 • eBay • fraud detection • graph algorithms • Graph Analytics • identity and access management • Network Monitoring • real-time recommendations • Social Networks
Powering Recommendations with a Graph Database: A Rapid Retail Example
By Jocelyn Hoppa
September 3, 2018|Reading time: 5 minutes
It’s one thing to say that Neo4j streamlines real-time recommendations; it’s another to show you the code so you can see for yourself. In this series, we discuss how real-time recommendations support a number of different use cases, from product… Read more →
Explore: cypher • entity-relationship diagram • facebook • graph database • graph technology • neo4j • real-time recommendations • Recommendations • Retail Recommendations • schema
Powering Recommendations with a Graph Database: Proven Business Benefits [+ Case Studies]
By Jocelyn Hoppa
August 27, 2018|Reading time: 5 minutes
Relevant, real-time recommendations drive revenue, but they are challenging to deliver. That’s because good recommendations require bringing together so much data, surfacing the relationships between all that data and delivering just the right suggestion in context and in the moment.… Read more →
Explore: Connected Data • data architecture • eBay • graph database • pricing engine • rdbms • real-time recommendations • Recommendations • sql • Walmart
Powering Recommendations with a Graph Database: Connect Buyer and Product Data
By Jocelyn Hoppa
August 20, 2018|Reading time: 3 minutes
Effective recommendations increase revenue and drive up average order value. But delivering highly relevant, real-time recommendations requires as much context as possible. Connecting the user to the perfect recommendation is an art. In this three-part series, we explore using recommendations… Read more →
Explore: customer relationship management • graph database • graph technology • nosql • personalized promotions • product recommendations • rdbms • real-time recommendations • Recommendations • relational database
Retail & Neo4j: Personalized Promotion & Product Recommendations
By Bryce Merkl Sasaki
November 6, 2017|Reading time: 6 minutes
Today’s retailers face a number of complex and emerging challenges. Thanks to lower overhead and higher volume, online behemoths like Amazon can deliver products faster and at a lower price, driving smaller retailers out of business. In order to compete,… Read more →
Explore: Connected Data • Cyber Monday • ecommerce • graph technology • personalized promotion • product recommendations • real-time recommendations • Recommendation Engine • Retail • Walmart
This Week in Neo4j – 2 April 2017
By Mark Needham
April 2, 2017|Reading time: 5 minutes
Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days. It’s a varied episode this week – we’ve got a worm’s neuronal wiring graph, bitcoin explorers,… Read more →
Explore: Bitcoin • datakind • emil eifrem • graph visualization • Jim Webber • ontology • real-time recommendations • twin4j • user-defined procedures
Who Cares What Beyoncé Ate for Lunch?
By Rachel Howard
November 16, 2016|Reading time: 11 minutes
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… Read more →
Explore: Beyoncé • CDC • center for disease control • data model • graph data model • graphconnect • r • real-time recommendations • recommendation algorithm • Recommendation Engine
From the Neo4j Community: February 2016
By Bryce Merkl Sasaki
March 8, 2016|Reading time: 3 minutes
In the Neo4j community last month, love was in the air. That love expressed itself as more nodes than ever in our community content. From articles and podcasts to GraphGists and other projects, our global graph of community members keeps… Read more →
Explore: cypher • data pipeline • elasticsearch • fraud detection • graph database • graph visualization • Master Data Management • metadata management • Neo4j Community • real-time recommendations
Your Perfect Mix Tape for Original Art: Artfinder + Neo4j [Community Post]
By Bryce Merkl Sasaki
February 25, 2016|Reading time: 4 minutes
[As community content, this post reflects the views and opinions of the particular author and does not necessarily reflect the official stance of Neo4j.] They say that that good artists copy, but great artists steal, right? At Artfinder, the global… Read more →
Explore: art • art recommendations • artfinder • collaborative filtering • cypher • graph database • machine learning • neo4j • real-time recommendations • Recommendation Engine
The 5-Minute Interview: Scott David, World Economic Forum
By Bryce Merkl Sasaki
January 22, 2016|Reading time: 6 minutes
This week’s 5-minute interview is with Scott David, the Director of Information Interaction at the World Economic Forum. I caught up with Scott David for a video interview at GraphConnect San Francisco. Q: Please tell us a little bit about… Read more →
Explore: 5-minute interview • cypher • data model • global issues • GraphAware • graphconnect • neo4j • real-time recommendations • transformation map • world economic forum
Neo4j Doc Manager: Polyglot Persistence for MongoDB & Neo4j
By Bryce Merkl Sasaki
October 29, 2015|Reading time: 6 minutes
[Editor’s Note:] This Neo4j Lab has been deprecated. The code is available in our GitHub project, but is no longer actively maintained. When building scalable applications, developers have a myriad of technologies to choose from, especially when choosing a database… Read more →
Explore: data model • document database • mongo connector • MongoDB • neo4j • polyglot persistence • product catalog • property graph • property graph model • real-time recommendations
The Future of Recommendation Engines: Graph-Aided Search
By Bryce Merkl Sasaki
October 6, 2015|Reading time: 4 minutes
Editor’s Note: GraphAware is a Silver sponsor of GraphConnect San Francisco. Register for GraphConnect to meet Michal and other sponsors in person. For the last couple of years, Neo4j has been increasingly popular as the technology of choice for people… Read more →
Explore: Connected Data • elasticsearch • graph database • neo4j • open source software • real-time recommendations • Recommendation Engine • Search Engine • social network • Solr
Graph Databases in the Enterprise: Real-Time Recommendation Engines
By Bryce Merkl Sasaki
September 28, 2015|Reading time: 3 minutes
Whether your enterprise operates in the retail, social, services or media sector, offering your users highly targeted, real-time recommendations is essential to maximizing customer value and staying competitive. Unlike other business data, recommendations must be inductive and contextual in order… Read more →
Explore: browsing history • eBay • Graph Databases • logistics • product recommendations • purchase history • real-time recommendations • Recommendation Engine • use case • Walmart
Congratulations to Aurelius, Välkommen to DataStax!
By Emil Eifrem, Chief Executive Officer
February 5, 2015|Reading time: 3 minutes
Congratulations to Aurelius on the news of your recent acquisition! The Aurelius team has always been our companions in promoting the value of relationships in data, and I wish you all the best as you embark upon the journey of… Read more →
Explore: Aurelius • Data Relationships • Datastax • fraud detection • graph data analysis • graph database • industry growth • real-time recommendations • supply chain management • Titan