Semi-supervised learning of word embeddings
US9947314B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 21, 2017 |
| Grant date | Apr 17, 2018 |
| Priority date | — |
| Expiry date | Feb 21, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Software that trains an artificial neural network for generating vector representations for natural language text, by performing the following steps: (i) receiving, by one or more processors, a set of natural language text; (ii) generating, by one or more processors, a set of first metadata for the set of natural language text, where the first metadata is generated using supervised learning method(s); (iii) generating, by one or more processors, a set of second metadata for the set of natural language text, where the second metadata is generated using unsupervised learning method(s); and (iv) training, by one or more processors, an artificial neural network adapted to generate vector representations for natural language text, where the training is based, at least in part, on the received natural language text, the generated set of first metadata, and the generated set of second metadata.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.