Pushing items to users based on a reinforcement learning model
US10902298B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 9, 2020 |
| Grant date | Jan 26, 2021 |
| Priority date | — |
| Expiry date | Mar 9, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/046
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This disclosure is related to determining an item push list for a user based on a reinforcement learning model. In one aspect, a method includes obtaining M first item lists that have been predetermined for a first user. Each first item list includes i−1 items. For each first item list, an ith state feature vector is obtained. The ith state feature vector includes a static feature and a dynamic feature. The ith state feature vector is provided as input to the reinforcement machine learning model. The reinforcement model outputs a weight vector including weights of sorting features. A sorting feature vector of each item in a candidate item set corresponding to the first item list is obtained. The sorting feature vector includes feature values of sorting features. M updated item lists are determined for the first item lists based on a score for each item in M candidate item sets.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.