Method and system for determining new categories with which a target user has not interacted

Abstract

Various embodiments attempt to predict items in a new product category that may be of interest to a particular user when the user has not interacted with or made purchases in that product category. In accordance with various embodiments of the present disclosure, this is accomplished by training machine learning models, such as deep neural networks, using both the historical purchase data from the particular user as well as the historical purchase data from many other users to infer what new category of items the particular user might be interested in. In some embodiments, the previous purchase data of the other users are used to construct a graph, and the graph is used to train the machine learning model rather than the raw data. The graph can represent the entirety of the previous purchase data with less actual data, thereby requiring less memory and other computational resources.