Trained sequence-to-sequence conversion of database queries
US11921711B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 6, 2020 |
| Grant date | Mar 5, 2024 |
| Priority date | — |
| Expiry date | Apr 5, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems are provided for sequence-to-sequence conversion from unstructured search queries to structured database queries, so that lay persons may retrieve information from relational databases without specialized knowledge of database query languages. An encoder module and a decoder module of a learning model are trained to convert an unstructured search query to an intermediate feature vector by computing co-attention and self-attention based on a context string and a database schema, encoding the database schema in the context string by application of self-attention between the context string containing tokens of the database schema with learned structural attention heads which relate the token to logic of the database. Training is performed using labeled training datasets which include structured database queries which are normalized by parsing into a semantic representation thereof, followed by linearization.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.