Avoiding sentiment model overfitting in a machine language model
US9881000B1 · kind B1 · utility
1Cited by
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18Claims
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Key dates
| Filing date | Jul 18, 2016 |
| Grant date | Jan 30, 2018 |
| Priority date | — |
| Expiry date | Jul 18, 2036 |
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.