Generating and applying a trained structured machine learning model for determining a semantic label for content of a transient segment of a communication
US10540610B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 27, 2016 |
| Grant date | Jan 21, 2020 |
| Priority date | — |
| Expiry date | Nov 6, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, apparatus, and computer-readable media are provided for analyzing a cluster of communications, such as B2C emails, to generate a template for the cluster that defines transient segments and fixed segments of the cluster of communications. More particularly, methods, apparatus, and computer-readable media are provided for generating and/or applying a trained structured machine learning model for a generated template that can be used to determine, for one or more transient segments of subsequent communications, a corresponding probability that a given semantic label is the correct semantic label for extracted content of the transient segment(s).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.