Machine learning based webinterface production and deployment system
US11386318B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 5, 2017 |
| Grant date | Jul 12, 2022 |
| Priority date | — |
| Expiry date | Nov 10, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Roughly described, the technology disclosed provides a so-called machine learned conversion optimization (MLCO) system that uses evolutionary computations to efficiently identify most successful webpage designs in a search space without testing all possible webpage designs in the search space. The search space is defined based on webpage designs provided by marketers. Website funnels with a single webpage or multiple webpages are represented as genomes. Genomes identify different dimensions and dimension values of the funnels. The genomes are subjected to evolutionary operations like initialization, testing, competition, and procreation to identify parent genomes that perform well and offspring genomes that are likely to perform well. Each webpage is tested only to the extent that it is possible to decide whether it is promising, i.e., whether it should serve as a parent for the next generation, or should be discarded.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.