Encoder using machine-trained term frequency weighting factors that produces a dense embedding vector
US11669558B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 28, 2019 |
| Grant date | Jun 6, 2023 |
| Priority date | — |
| Expiry date | Apr 6, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented technique generates a dense embedding vector that provides a distributed representation of input text. The technique includes: generating an input term-frequency (TF) vector of dimension g that includes frequency information relating to frequency of occurrence of terms in an instance of input text; using a TF-modifying component to modify the term-specific frequency information in the input TF vector by respective machine-trained weighting factors, to produce an intermediate vector of dimension g; using a projection component to project the intermediate vector of dimension g into an embedding vector of dimension k, where k is less than g. Both the TF-modifying component and the projection component use respective machine-trained neural networks. An application performs any of a retrieval-based function, a recognition-based function, a recommendation-based function, a classification-based function, etc. based on the embedding vector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.