Dimensional reduction of complex vectors in artificially intelligent solutions to compare similarity of natural language text
US11409752B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 4, 2020 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Feb 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A web-based tool performs records matching in response to a freeform text input, to find highly contextually-related sentences in a corpus of records. Each sentence in the corpus is converted into a full-size vector representation, and each vector's angle within space is measured. Each full-size vector is compressed to a smaller vector and a loss function is used to preserve for each vector the angle within the lower-dimensional space that existed for the higher-dimensional vector. Full-size and reduced vector representations are generated from the freeform text input. The reduced-size vector of the input is compared to those of the corpus of text to identify, in real-time, a set of vector nearest neighbors that includes, with high accuracy, representations of all records in the corpus similar to the input. Full-size vectors for the nearest neighbors are in turn retrieved and compared to the input, and ranked results are generated.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.