Identifying source datasets that fit a transfer learning process for a target domain
US11308077B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 21, 2020 |
| Grant date | Apr 19, 2022 |
| Priority date | — |
| Expiry date | Oct 13, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for quantifying a similarity between a target dataset and multiple source datasets and identifying one or more source datasets that are most similar to the target dataset is provided. The method includes receiving, at a computing system, source datasets relating to a source domain and a target dataset relating to a target domain of interest. Each dataset is arranged in a tabular format including columns and rows, and the source datasets and the target dataset include a same feature space. The method also includes pre-processing, via a processor of the computing system, each source-target dataset pair to remove non-intersecting columns. The method further includes calculating at least two of a dataset similarity score, a row similarity score, and a column similarity score for each source-target dataset pair, and summarizing the calculated similarity scores to identify one or more source datasets that are most similar to the target dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.