Systems and methods for multidimensional knowledge transfer for click through rate prediction
US12236457B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 3, 2022 |
| Grant date | Feb 25, 2025 |
| Priority date | — |
| Expiry date | Jul 18, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A multidimensional knowledge transfer model for predicting CTR of a computational ad, the multidimensional knowledge transfer model comprises: a pre-processor for building an ad group node graph based on similarities among ad group nodes, an ad campaign node graph from merging the ad group node graph, and an ad account node graph from merging the ad campaign node graph. The multidimensional knowledge transfer model further comprises a multi-knowledge CTR prediction model for each of the ad account, ad campaign, and ad group layers. The multi-knowledge CTR prediction model predicts the respective node's CTR from the ad account node graph, ad campaign node graph, or ad group node graph, features of the audience group, and features of the node having its CTR predicted appended with the hidden vector of its parent node extracted from the upper layer multi-knowledge CTR prediction model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.