Graph-based semi-supervised learning of structured tagging models
US8560477B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2010 |
| Grant date | Oct 15, 2013 |
| Priority date | — |
| Expiry date | May 8, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2323
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for graph-based semi-supervised learning of structured tagging models. In one aspect, a method includes creating a graph having a plurality of unique vertices in which vertices in a first set of vertices represent n-grams that are each associated with a respective part-of-speech and that were derived from labeled source domain text, and in which vertices in a different second set of vertices represent n-grams that are not associated with a part-of-speech and that were derived from unlabeled target domain text. A respective measure of similarity is calculated between the vertices in each of the pairs based at least partially on a distance between the respective features of the pair used to weight a graph edge between the pair.
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