Machine learning technique for recommendation of courses in a social networking service based on confidential data
US11188834B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2016 |
| Grant date | Nov 30, 2021 |
| Priority date | — |
| Expiry date | May 12, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q2220/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example, each of a plurality of members of social networking service is mapped to a weighted skill vector, each weighted skill vector including a list of skills for the member with an associated weight indicating strength of the skill. Members of the social networking service that belong to an industry are aggregated to obtain a weighted matrix of members and skills along with compensation vectors indicating compensation for each of the members in the matrix. The weighted matrix of users and skills and corresponding compensation vectors is used to train a machine learning skill monetary value prediction model to output a predicted monetary value for one or more skills contained in a candidate vector fed to the machine learning skill monetary value prediction model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.