Training systems and methods for sequence taggers
US9792560B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 17, 2015 |
| Grant date | Oct 17, 2017 |
| Priority date | — |
| Expiry date | Dec 22, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for or training as sequence tagger, such as conditional random field model. More specifically, the systems and methods train a sequence tagger utilizing partially labeled data from crowd-sourced data for a specific application and partially labeled data from search logs. Further, the systems and methods disclosed herein train a sequence tagger utilizing only partially labeled by utilizing a constrained lattice where each input value within the constrained lattice can have multiple candidate tags with confidence scores. Accordingly, the systems and methods provide for a more accurate sequence tagging system, a more reliable sequence tagging system, and a more efficient sequence tagging system in comparison to sequence taggers trained utilizing at least some fully-labeled training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.