Identifying similar content in a multi-item embedding space
US11574020B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 12, 2019 |
| Grant date | Feb 7, 2023 |
| Priority date | — |
| Expiry date | Feb 7, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/958
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for identifying content for an input query are presented. A mapping model is trained to map elements of an input query embedding vector for a received query into one or more elements of a destination embedding vector. In response to receiving an input query, an input query embedding vector is generated that projects into an input query embedding space. The input query embedding vector is processed by the mapping model to map the input query embedding vector into one or more elements of a destination embedding vector in a destination embedding space, resulting in a partial destination embedding vector. Items of a corpus of content are projected into the destination embedding space and the partial destination embedding vector is also projected into the destination embedding space. A similarity measure determines the most-similar items to the partial destination embedding vector and at least some of the most-similar items are returned in response to the input query.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.