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 go hands on with Neo4j Bloom, there’s a new release of Popoto – the visual query builder for Neo4j, we learn how to build a personalised recommender as well as parse Neo4j’s query log, and more.


This week’s featured community member is Thomas Frisendal, Graph Data Architect and Visual Data Modeler.

Thomas Frisendal - This Week’s Featured Community Member

Thomas Frisendal – This Week’s Featured Community Member

Thomas has been part of the Neo4j community for several years and has written multiple articles about data modelling with graphs and knowledge graphs.

He published a new article this week in which he shows how to use the betweenness and closeness centrality graph algorithms to explore data models.

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

Neo4j Bloom: Hands On with the Beer Graph


In last week’s version of TWIN4j we mentioned the announcement of Neo4j Bloom, a graph communication and data visualization product that we’ve been working on.



Since then Rik has been busy putting it through its paces with a two part tutorial in which he shows how to explore the Belgian Beer Graph.

He gives an introduction to the basic functionality before explaining the more advanced custom search phrases feature. This post will certainly whet your appetite for the types of exploration you’ll be able to do on your own datasets in the coming months.

If you don’t have time to work through the blog posts you can always watch the accompanying 5 minute video linked above.

Popoto 2.0 Released


Staying in the world of graph visualization, this week Ciminera Frederic released version 2.0 of Popoto, a visual query builder for Neo4j.

This release sees an update to d3 v5, donut representation of node relations around the node in graph, and support for ‘not’, ‘and’, ‘or’ constraints in graph.

You can find a list of popoto example applications in the popoto-examples repository. Hopefully one of them will grab your attention.

Building a personalized recommender, Visualizing Game of Thrones,


    • Grace Tenorio shared the slides from her talk titled ‘Building a Recommender Using Neo4j’. Grace shows how to build a recommendation engine for an online grocery store using different approaches including user-user collaborative filtering and K nearest neighbours.
    • It really is the week for graph visualization. Ashish Chaudhary has written a blog post in which he explores the Game of Thrones universe using the vis.js library.
    • My colleague Benoit Simard rounds off the week of graph visualization with a post showing how to display and customize a graph in a browser with the help of SigmaJS. In the first half of the post Benoit explains how to build a graph visualization using SigmaJS directly and in the second half he shows a much easier way using a library he’s built called NeoSig which integrates Neo4j and SigmaJS.
    • Vindya Hemali has posted the 2nd part of a Neo4j series. This post explains the Neo4j Desktop in detail and includes a guide to get you up and running.

From the Knowledge Base: Parsing query.log


This week from the Neo4j Knowledge Base we have an entry that shares a script that parses the query log available in the Neo4j Enterprise Edition.

The script summarises the total number of queries, their running time, the date and time of the first and last queries, and more.

If you want to understand what’s happening on your Neo4j server this is a good place to start.

Tweet of the Week


My favourite tweet this week was by Leticia Becker:

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

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

Cheers, Mark

 

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About the Author

Mark Needham, Developer Relations Engineer

Mark Needham Image

Mark Needham is a graph advocate and developer relations engineer at Neo4j.

As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in Neo4j 3.1. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com. He tweets at @markhneedham.


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