Index-based technique friendly CTR prediction and advertisement selection
US8380570B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 27, 2009 |
| Grant date | Feb 19, 2013 |
| Priority date | — |
| Expiry date | Jun 17, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0202
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
Methods and systems are provided for click through rate prediction and advertisement selection in online advertising. Methods are provided in which output information from a feature-based machine learning model is utilized. The output information includes predicted click through rate information. The output information is used to form a matrix. The matrix is modeled using a latent variable model. Machine learning techniques can be used in determining values for unfilled cells of one or more model matrices. The latent variable model can be used in determining predicted click through rate information, and in advertisement selection in connection with serving opportunities.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.