Techniques for automated self-adjusting corporation-wide feature discovery and integration
US11475374B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 4, 2020 |
| Grant date | Oct 18, 2022 |
| Priority date | — |
| Expiry date | Oct 20, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems and methods for a self-adjusting corporation-wide discovery and integration feature of a machine learning system that can review a client's data store, review the labels for the various data schema, and effectively map the client's data schema to classifications used by the machine learning model. The various techniques can automatically select the features that are predictive for each individual use case (i.e., one client), effectively making a machine learning solution client-agnostic for the application developer. A weighted list of common representations of each feature for a particular machine learning solution can be generated and stored. When new data is added to the data store, a matching service can automatically detect which features should be fed into the machine-learning solution based at least in part on the weighted list. The weighted list can be updated as new data is made available to the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.