Tracking provenance in data science scripts
US11775862B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 14, 2020 |
| Grant date | Oct 3, 2023 |
| Priority date | — |
| Expiry date | Jun 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system enables tracking machine learning (“ML”) model data provenance. In particular, a computing device is configured to accept ML model code that, when executed, instantiates and trains an ML model, to parse the ML model code into a workflow intermediate representation (WIR), to semantically annotate the WIR to provide an annotated WIR, and to identify, based on the annotated WIR and ML API corresponding to the ML model code, data from at least one data source that is relied upon by the ML model code when training the ML model. A WIR may be generated from an abstract syntax tree (AST) based on the ML model code, generating provenance relationships (PRs) based at least in part on relationships between nodes of the AST, wherein a PR comprises one or more input variables, an operation, a caller, and one or more output variables.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.