Customer profile learning based on semi-supervised recurrent neural network using partially labeled sequence data
US11093818B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 11, 2016 |
| Grant date | Aug 17, 2021 |
| Priority date | — |
| Expiry date | Jun 11, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0895
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system are provided. The method includes receiving by a computer having a processor and a memory, sequence data that includes labeled data and unlabeled data. The method further includes generating, by the computer having the processor and the memory, a recurrent neural network model of the sequence data, the recurrent neural network model having a recurrent layer and an aggregate layer. The recurrent neural network model feeds sequences generated from the recurrent layer into the aggregate layer for aggregation, stores temporal dependencies in the sequence data, and generates labels for at least some of the unlabeled data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.