Language agnostic machine learning model for title standardization
US11610109B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 26, 2018 |
| Grant date | Mar 21, 2023 |
| Priority date | — |
| Expiry date | Dec 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example embodiment, a system is provided whereby a machine learning model is trained to predict a standardization for a given raw title. A neural network may be trained whose input is a raw title (such as a query string) and a list of candidate titles (either title identifications in a taxonomy, or English strings), which produces a probability that the raw title and each candidate belong to the same title. The model is able to standardize titles in any language included in the training data without first having to perform language identification or normalization of the title. Additionally, the model is able to benefit from the existence of “loan words” (words adopted from a foreign language with little or no modification) and relations between languages.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.