Apparatus and method for transforming unstructured data sources into both relational entities and machine learning models that support structured query language queries
US11809417B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 28, 2021 |
| Grant date | Nov 7, 2023 |
| Priority date | — |
| Expiry date | Feb 9, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A non-transitory computer readable storage medium has instructions executed by a processor to receive from a network connection different sources of unstructured data. An entity is formed by combining one or more sources of the unstructured data, where the entity has relational data attributes. A representation for the entity is created, where the representation includes embeddings that are numeric vectors computed using machine learning embedding models, including trunk models, where a trunk model is a machine learning model trained on data in a self-supervised manner. An enrichment model is created to predict a property of the entity. A query is processed to produce a query result, where the query is applied to one or more of the entity, the embeddings, the machine learning embedding models, and the enrichment model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.