Generating navigational target recommendations using parallel neural networks

Abstract

Techniques for generating navigational target recommendations for a user are disclosed. A system propagates sets of user attributes through one neural network and sets of navigational target attributes through another neural network. The neural networks are configured to generate, as outputs, vectors mapped to a same vector space. The system trains the neural networks to identify relationships between the sets of user attributes and the sets of navigational targets. Once the neural networks have been trained, the system generates an embedding for a user by propagating the user's attributes through the trained user attribute neural network. The system also generates embeddings for different navigational targets by propagating the attributes for the different navigational targets through the navigational target neural network. The system identifies relationships between the user and the navigational targets based on the embeddings. The system generates recommendations for navigational targets for the user based on the identified relationships.