Machine learning technique for recommendation of skills in a social networking service based on confidential data
US10535018B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2016 |
| Grant date | Jan 14, 2020 |
| Priority date | — |
| Expiry date | Feb 21, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example embodiment, each of a plurality of members of a 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 a strength of the skill. Members of the social networking service who 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 members and skills and corresponding compensation vectors are used to train a machine learning skill monetary value prediction model to output a predicted monetary value for a skill contained in a candidate vector fed to the machine learning skill monetary value prediction model. A recommendation is provided to a member of one or more skills to add based on output of the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.