System and method for large-scale multi-label learning using incomplete label assignments
US10325220B2 · kind B2 · utility
3Cited by
1References
27Claims
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Key dates
| Filing date | Nov 17, 2014 |
| Grant date | Jun 18, 2019 |
| Priority date | — |
| Expiry date | May 5, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
At least one label prediction model is trained, or learned, using training data that may comprise training instances that may be missing one or more labels. The at least one label prediction model may be used in identifying a content item's ground-truth label set comprising an indicator for each label in the label set indicating whether or not the label is applicable to the content item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.