DoorDash’s retail catalog is a centralized dataset of essential product information for all products sold by new verticals merchants – merchants operating a business other than a restaurant, such as a grocery, a convenience store, or a liquor store.
Tag Archives: Inventory Intelligence
Augmenting Fuzzy Matching with Human Review to Maximize Precision and Recall
Even state-of-the-art classifiers cannot achieve 100% precision.
Using Triplet Loss and Siamese Neural Networks to Train Catalog Item Embeddings
Understanding the contents of a large digital catalog is a significant challenge for online businesses, but this challenge can be addressed using self-supervised neural network models.
Uncovering Online Delivery Menu Best Practices with Machine Learning
Photo Credit: Jeff Marini
Restaurants on busy thoroughfares can use many elements to catch a customer’s eye, but online ordering experiences mostly rely on the menu to generate sales.
Using a Human-in-the-Loop to Overcome the Cold Start Problem in Menu Item Tagging
Companies with large digital catalogs often have lots of free text data about their items, but very few actual labels, making it difficult to analyze the data and develop new features.
Building a system that can support machine learning (ML)-powered search and discovery features while simultaneously being interpretable enough for business users to develop curated experiences is difficult.