Enhanced validity modeling using machine-learning techniques
US11966856B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2020 |
| Grant date | Apr 23, 2024 |
| Priority date | — |
| Expiry date | Feb 22, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.