In the " Building a Recommendations Engine Using Spring Boot and Slash GraphQL" article, the recently released  Slash GraphQL hosted GraphQL backend by  Dgraph was utilized as a system of record for a Java-based recommendations engine.

A graph datastore is a great fit for a use case such as a recommendation engine, where the relationships between the data are just as important as the data itself. And using Slash GraphQL allowed me to quickly get a fully managed GraphQL database up and running with minimal effort.

The article also provided insight on how the Slope One family of collaborative filtering algorithms could be utilized to predict the level of product interest based upon existing ratings. In short, the Slope One Ratings Algorithm would be at the heart of the recommendations engine.

The article concluded by providing RESTful URIs in the Spring Boot recommendation engine to provide recommendations from the data stored in the Dgraph Slash GraphQL SaaS service offering.

This article will take things a little further and introduce an Angular client to present this data in a way that’s easier to consume…and hopefully appreciate.

Enhancements to the Data Domain

While the original article showed how the recommendations engine would work, I felt like my original data sample provided too many ratings for a few of the sample customers. Additionally, I felt like I needed to expand the number of artists used for this second example.

#java #web dev #spring boot #angular #graphql #dgraph