Deep learning-based revenue-per-click prediction model framework
US11710148B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 31, 2021 |
| Grant date | Jul 25, 2023 |
| Priority date | — |
| Expiry date | Feb 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform extracting meta features for an item to generate sparse feature embeddings for the item; reducing, using a multilayer perceptron, a dimension of the sparse feature embeddings to generate a representation vector for the meta features; extracting, using a recurrent neural network, sequential data from dense traffic features for the item over a period of time; and inputting the representation vector for the meta features and the sequential data from the dense traffic features into a multilayer neural network with a rectified linear unit (ReLU) activation function and a scoring layer to generate one or more performance metrics for the item. Other embodiments are disclosed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.