Differentiable user-item co-clustering
US11636394B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Jun 25, 2020 |
| Grant date | Apr 25, 2023 |
| Priority date | — |
| Expiry date | Mar 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present concepts relate to a differentiable user-item co-clustering (“DUICC”) model for recommendation and co-clustering. Users' interaction with items (e.g., content) may be centered around information co-clusters—groups of items and users that exhibit common consumption behavior. The DUICC model may learn fine-grained co-cluster structures of items and users based on their interaction data. The DUICC model can then leverage the learned latent co-cluster structures to calculate preference stores of the items for a user. The top scoring items may be presented to the user as recommendations.
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