Graph-Powered Recommendations: A Framework for Faster Development
By David Penick
June 1, 2020 3 mins read
Read blog three in Neo4j’s five-part series on how graph-powered recommendation engines drive value for enterprise businesses.
Explore: blog series • graph algorithms • graph database • graph powered recommendation • graph recommendation engine • Neo4j Recommendation Framework • Personalization • personalized recommendations • Recommendation Engine
Creating an Intelligent Recommendation Framework
By Jocelyn Hoppa
September 5, 2019 4 mins read
Read this blog to learn more about the benefits of using a native graph database to build a real-time recommendation engine with personalization.
Explore: centrality algorithms • community detection • cypher • data model • graph algorithms • graph database • graph model • GraphQL API • index free adjacency • Intelligent Recommendations Framework
Mapping Ontologies in Graphs for Personalization
By Jocelyn Hoppa
February 20, 2019 14 mins read
Editor’s Note: This presentation was given by Irene Iriarte-Carretero at GraphConnect San Francisco in October 2016. Presentation Summary Gousto is a UK-based recipe box service that uses Neo4j to map recipe ontologies so it can provide more personalized recommendations to… Read more →
Explore: collaborative filtering • content-based filtering • customer journey • gousto • graph ontology • graphconnect • hybrid recommender system • LightFM • Personalization • Recommendation Engine
11 Must-See Speakers at GraphConnect 2018 in New York City
By Bryce Merkl Sasaki
August 24, 2018 2 mins read
There are a lot of great reasons to attend GraphConnect 2018, but one of the best reasons is that every year we feature a fresh, new lineup of the world’s best graph experts sharing their experiences on how graph database… Read more →
Explore: ai • data governance • data management • Data Scientist • graphconnect • machine learning • Master Data Management • Personalization • predictive analytics • Recommendations