Learning Item-Interaction Embeddings for User Recommendations

Understand

Industry-scale recommendation systems have become a cornerstone of the e-commerce shopping experience.

• For Etsy, an online marketplace with over 50 million handmade and vintage items, users come to rely on personalized recommendations to surface relevant items from its massive inventory.
• One hallmark of Etsy's shopping experience is the multitude of ways in which a user can interact with an item they are interested in: they can view it, favorite it, add it to a collection, add it to cart, purchase it, etc.
• We hypothesize that the different ways in which a user interacts with an item indicates different kinds of intent.