This Week in Neo4j – Recommendations with Personalized PageRank, Solving the bucket-filling problem, Deep Text Understanding

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.

This week we have recommendations with Personalized PageRank, Solving the bucket-filling problem, Deep Text Understanding, a new GraphQL book, Thinking in Graph for security, and more!

This week’s featured community member is Scott Sosna, Software Senior Principal Engineer at Dell EMC.

Scott Sosna – This Week’s Featured Community Member

Scott has been using Neo4j to explore different open data sets, and has already presented his work at the Central Iowa Java Users Group, DevoxxUK, and most recently at the DubJUG.

Scott explores how to use Neo4j for traffic data, the London tube network, US government public disclosure filings, and more! You can find some of Scott’s other graph datasets on GitHub.

On behalf of the Neo4j community, thanks for all your work Scott!

Neo4j Bloom Data Visualization for Everyone

This week Jeff Morris presented a webinar about Neo4j Bloom, a data visualization tool on the Neo4j Graph Platform.

Jeff explains why graph visualization is such an important tool for business users and then describes the features that Neo4j Bloom has to offer, such as near natural language search, code free graph changes, and direct graph interactions. Finally he shows how to use Bloom on several different datasets.

If you’re attending GraphConnect NYC 2018 next week (20/21 September), you’ll be able to learn more about Bloom in the following sessions:

Article recommendations using Personalized Pagerank and GraphAware NLP

Tomaz Bratanic has written a blog post explaining how to use the Personalized PageRank algorithm that was added in the most recent release of the Graph Algorithms library.

In the post Tomaz goes through a worked example showing how to build an article recommender system that finds the best articles or papers for a keyword given the context of the researcher asking the question.

As well as using the Graph Algorithms library, Tomaz also uses GraphAware NLP to build a graph of key phrases in each paper.

Solving the bucket-filling problem with Neo4j

Vince Bickers explains how to solve the bucket-filling problem by creating a state machine where each state is a node, and transitions between states are relationships.


Vince shows how to build out the state machine using various Cypher queries, ensuring that none of the rules of the game are broken as we do this. He then shows how to find all possible solutions for the problem using Cypher’s shortest path algorithm.

GraphQL Book Release, Thinking in Graphs, Virtual Nodes and Relationships

Releases: 3.4.7 AMIs for AWS and Java Driver 1.7.0-beta02

David Allen announced the release of New AMIs for Neo4j 3.4.7 on AWS. These AMIs come ready made with APOC and Graph Algorithms so that you can start building your graph based applications as quickly as possible.

Deep Text Understanding, Semantic Analysis, Micrometer and Spring Boot

On the podcast: Karin Wolok

This week on the Graphistania podcast, Rik interviewed Karin Wolok, Neo4j’s Program Manager of Community Development and Enablement.

They talk about the new Neo4j forum that we launched 3 weeks ago, how Karin got into graph databases, and the programs Karin is building out for the Neo4j community.

Next Week

What’s happening next week in the world of graph databases?

Date Title Group

September 17th 2018

Algorithms, Graphs and Awesome Procedures

GraphDB Sydney

September 20th 2018

GraphConnect 2018

Marriott Times Square, New York City

Tweet of the Week

My favourite tweet this week was by Jim Webber:

Don’t forget to RT if you liked it too.

That’s all for this week. Have a great weekend!

Cheers, Mark