Deep graph representation learning
US10482375B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 2, 2017 |
| Grant date | Nov 19, 2019 |
| Priority date | — |
| Expiry date | Mar 31, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/426
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of deep graph representation learning includes: calculating a plurality of base features from a graph and adding the plurality of base features to a feature matrix. The method further includes generating, by a processing device, a current feature layer from the feature matrix and a set of relational feature operators, wherein the current feature layer corresponds to a set of current features, evaluating feature pairs associated with the current feature layer, and selecting a subset of features from the set of current features based on the evaluated feature pairs. The method further includes adding the subset of features to the feature matrix to generate an updated feature matrix.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.