Artificial intelligence system using unsupervised transfer learning for intra-cluster analysis
US11514321B1 · kind B1 · utility
5Cited by
15References
20Claims
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Key dates
| Filing date | Jun 12, 2020 |
| Grant date | Nov 29, 2022 |
| Priority date | — |
| Expiry date | May 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Entity record pairs are extracted from a selected cluster of entity records. Attribute value pairs are obtained from the entity record pairs. Labels are assigned to the attribute value pairs based at least in part on entity-level similarity scores of the entity records from which the attribute value pairs were obtained. A machine learning model is trained, using a data set which includes at least some attribute value pairs to which the labels are assigned, to generate attribute similarity scores for pairs of attribute values.
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