Composite machine learning system for label prediction and training data collection
US11816544B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 16, 2021 |
| Grant date | Nov 14, 2023 |
| Priority date | — |
| Expiry date | Dec 28, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q40/123
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides a composite machine learning system for a transaction labeling service. A transaction labeling service receives at least one descriptive string describing a transaction associated with a user. The service identifies a preliminary grouping from a generalized scheme. The service extracts a set of N-grams from the descriptive string and converts the N-grams and the preliminary grouping into a set of features. A machine learning model determines a label from a labeling scheme for the transaction based on the features. User input related to the label includes an accuracy indicator and a reliability indicator. If the reliability indicator satisfies a reliability condition, a set of training data for the machine learning model is updated based on the descriptive string and the label. The machine learning model is then trained against the updated set of training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.