Global graph-based classification techniques for large data prediction domain
US12399937B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2023 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Oct 31, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/9024
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various embodiments of the present disclosure provide data storage, processing, and prediction techniques for providing predictive insights within large data prediction domains. The techniques may include generating, using a plurality of source tables for a prediction domain, a global graph for the prediction domain. The techniques may include generating, using a graph-based machine learning model, a plurality of node-level weights for the plurality of graph nodes based on a plurality of node attributes corresponding to the plurality of graph nodes. The techniques may include generating, using the graph-based machine learning model, a plurality of semantic-level weights for the plurality of weighted edges based on a designated predictive task for the global graph. The techniques may include generating plurality of graph node embeddings and initiating the performance of the designated predictive task based on the plurality of graph node embeddings.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.