SYSTEMS AND METHODS USING DEEP JOINT VARIATIONAL AUTOENCODERS
Systems and methods for generating top-k recommendation using latent space representations generated by deep joint variational autoencoder processes are disclosed. A user identifier is received and a set of prior interactions associated with the user identifier is obtained. A set of latent space rep...
Gespeichert in:
Hauptverfasser: | , , , , , |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Systems and methods for generating top-k recommendation using latent space representations generated by deep joint variational autoencoder processes are disclosed. A user identifier is received and a set of prior interactions associated with the user identifier is obtained. A set of latent space representations of the set of prior interactions is generated using a trained inference model. The trained inference model includes a joint variational autoencoder model. A set of k-recommended items is generated based on a comparison of the set of latent space representations of the set of prior interactions and a set of latent space representations of one or more items. A user interface including the set of k-recommended items is generated. |
---|