Composite machine-learning system for label prediction and training data collection
US10984340B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 31, 2017 |
| Grant date | Apr 20, 2021 |
| Priority date | — |
| Expiry date | Sep 7, 2039 |
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.