Avoiding sentiment model overfitting in a machine language model
US10496751B2 · kind B2 · utility
0Cited by
0References
18Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Dec 13, 2017 |
| Grant date | Dec 3, 2019 |
| Priority date | — |
| Expiry date | Jul 18, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q50/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided are techniques for avoiding sentiment model overfitting in a machine language model. A current list of keywords in a current sentiment model can be updated to create a proposed list of keywords in a proposed sentiment model. Machine-generated sentiment results, based on the proposed sentiment model, are presented to identify model overfitting, without revising the current set of keywords. The proposed set of keywords can be edited, and when overfitting is not present, the current list of keywords is replaced by the proposed list of keywords.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.