It’s a fundamental question for any eCommerce business looking to implement advanced search and discovery features:
What’s the process for building a recommendation system? How can you compute similarities between objects to serve products that users are likely to purchase?
In this video, Constructor’s data science team will walk you through some of the most influential papers on building recommendation systems, the pros and cons of the methods discussed in each paper, and much more — from the basic co-occurrence methods used in 1994 to Graph Convolutional Neural Networks used today like PinSage.
Take a look: