We’re all familiar with recommendations in a number of different areas of our lives. Recommendations for social media connections, e-commerce products, or streaming media content are ubiquitous. Perhaps less well known are applications for recommendations in different contexts - like education, HR, fraud detection, business process management, or offender rehabilitation. In this talk we will discuss some of these recommendations use cases in more detail, and look at how graph data can be used to model each domain and power a recommendations engine. We’ll also see an example use case demonstrated using Neo4j.
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Graphs for recommendation engines: Looking beyond social, retail, and media
Originally from the USA but now living in the UK, Joe Depeau has over 20 years of varied experience in the IT industry across a number of domains and specialties. Most recently, Joe has focused on technical pre-sales and solution architecture in the data and analytics space. When not geeking out over data and technology he enjoys camping, hiking with his dog, tending to his garden, reading, and playing boardgames and RPGs. He also bakes a mean cheesecake.