Academic sources for Neo4j white papers?

Hi everyone,

I'm currently working through some of Neo4j's existing white papers and I'm wondering if there is some kind of list of academic references associated with them.

Currently the two papers I have of interest are " Financial Fraud Detection with Graph Data Science" By Amy E. Hodler and "Improving Machine Learning Predictions Using Graph Algorithms" By Amy E. Hodler. I'm also reading the Graph algorithm book provided by Neo4j.

In the first two white papers there are some quantitative statements (eg. "With graph data science, you detect more fraud in the data you already have without changing
your ML pipeline.") that I would love to find a cite-able paper for.

If anyone has other recommendations for comparative computation resources please feel free to send them to me. I definitely see the efficiency in graph approaches, but need some references for academic writing on the topic.

P.S. I will also post this to the discord.

Thank you in advance,
Dylan Loader

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Hello, @dylanloader !

Amy has some great articles! Here are some other resources I've found helpful.

"A Comparative Study of Network Modeling Using a Relational Database (e.g.
Oracle, MySQL, SQL Server) vs. Neo4j": https://mwdsi.decisionsciences.org/wp-content/uploads/2020/08/2017-MWDSI-Proceedings-Final-April-30.pdf#page=156

"A comparative evaluation of RDBMS and GDBMS for shortest path operations on pedestrian navigation data": A comparative evaluation of RDBMS and GDBMS for shortest path operations on pedestrian navigation data | IEEE Conference Publication | IEEE Xplore

As well as the book "Graph-Powered Machine Learning" by Dr. Alessandro Negro of GraphAware: Graph-Powered Machine Learning | GraphAware

Hope this helps!

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Hi Sarah,

Thanks a ton for the recommendations. I will give these a read over the next few days and report back!

Sincerely,
Dylan