Recommending content to subscribers
US12079289B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 8, 2022 |
| Grant date | Sep 3, 2024 |
| Priority date | — |
| Expiry date | Aug 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/906
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for recommending content to an online service subscriber are presented. For each subscriber, content items that were the subject of the subscriber's prior interactions are projected, via associated embedding vectors, into a content item embedding space. The content items, via their projections into the content item embedding space, are clustered to form a plurality of interest clusters for the subscriber. A representative embedding vector is determined for each interest cluster, and a plurality of these embedding vectors are stored as the representative embedding vectors for the subscriber. The online service, in response to a request for recommended content for a subscriber, selects a first representative embedding vector associated with the subscriber and identifies a new content item from a corpus of content items according to a similarity measure between the first representative embedding vector and an embedding vector associated with the new content item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.