Representation learning with side information
US12223274B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 29, 2021 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Feb 20, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A relational similarity determination engine receives as input a dataset including a set of entities and co-occurrence data that defines co-occurrence relations for pairs of the entities. The relational similarity determination engine also receives as input side information defining explicit relations between the entities. The relational similarity determination engine jointly models the co-occurrence relations and the explicit relations for the entities to compute a similarity metric for each different pair of entities within the dataset. Based on the computed similarity metrics, the relational similarity determination engine identifies a most similar replacement entity from the dataset for each of the entities within the dataset. For a select entity received as an input, the relational similarity determination engine outputs the identified most similar replacement entity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.