Hashing query and job posting features for improved machine learning model performance
US10565562B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 25, 2017 |
| Grant date | Feb 18, 2020 |
| Priority date | — |
| Expiry date | Dec 18, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q50/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example, a first hash function is performed on job posting features extracted from a job posting to obtain hashed job posting features. The hashed job posting features are stored in a forward-index corresponding to the job posting in the database. When a job search query is received from a first member of a social networking service, job search query features are extracted from the job search query and a second hash function is performed on the job search query features. The hashed job posting features and the hashed job search query features are fed to a job posting result ranking model trained via a machine learning algorithm to compare the hashed job posting features to the hashed job search query features to generate an application likelihood score indicating a likelihood that the first member will apply for a job corresponding to the job posting.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.