Client interest profiles and embeddings for a research organization
US11977965B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 19, 2023 |
| Grant date | May 7, 2024 |
| Priority date | — |
| Expiry date | May 19, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Computer systems and methods for a research organization compute interests of clients in research work product, and, using deep learning and embedding techniques, digitalize client interest profiles and research content entities. A first machine learning model is trained to compute client-interest scores from, at least in part, client engagement data. The computer system is also configured to compute embeddings for each of the clients and embeddings for each of certain research topics. The embeddings are computed using a second machine learning model, such as deep artificial neural network, such that embeddings for clients with similar interests are close, distance-wise, in a client embedding space, and such that embeddings for certain research topics with similar client engagements are close, distance-wise, in a research topic embedding space. The second machine learning model can be trained with both positive and negative training samples generated from the client-interest scores.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.