Graph & Beyond The Second Course #2.3: Recommendation Engine

Recommendation Systems are algorithms that suggest products, services, information to users based on analysis of data. The recommendation algorithms can derive from a variety of factors such as the history of the user, and how they rate the various items they have bought, watched, read, etc. As well as the behavior of similar users. A multitude of approaches has been developed over the years.

In this Lunch & Learn, we give an overview of the various approaches for recommending products/services as well as demo how these approaches can be implemented using both Search and Graph in ArangoDB.

About the Presenter:

Victor has 20+ years of experience in various technology companies in Silicon Valley, ranging from startups to large companies in Graph Databases, RDBMS, Full-Text Search, Enterprise Security, and AdTech.

Register for lunch break:

Victory Moey
Victory Moey