Deep learning using activity graph to detect abusive user activity in online networks
US11991197B2 · kind B2 · utility
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5References
20Claims
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Key dates
| Filing date | Mar 25, 2022 |
| Grant date | May 21, 2024 |
| Priority date | — |
| Expiry date | Jan 4, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example embodiment, a deep learning algorithm is introduced that operates on a transition matrix formed from user activities in an online network. The transition matrix records the frequencies that particular transitions between paths of user activity have occurred (e.g., the user performed a login activity, which has one path in the network, and then performed a profile view action, which has another path in the network). Each transition matrix corresponds to a different user's activities.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.