End-to-end deep collaborative filtering
US10824941B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 22, 2016 |
| Grant date | Nov 3, 2020 |
| Priority date | — |
| Expiry date | May 14, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A recommendation system generates recommendations for an online system using one or more neural network models that predict preferences of users for items in the online system. The neural network models generate a latent representation of a user and of a user that can be combined to determine the expected preference of the user to the item. By using neural network models, the recommendation system can generate predictions in real-time for new users and items without the need to re-calibrate the models. Moreover, the recommendation system can easily incorporate other forms of information other than preference information to generate improved preference predictions by including the additional information to generate the latent description of the user or item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.