Systems and methods for machine learning-based digital content clustering, digital content threat detection, and digital content threat remediation in machine learning-based digital threat mitigation platform
US11528290B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 6, 2022 |
| Grant date | Dec 13, 2022 |
| Priority date | — |
| Expiry date | Apr 6, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1416
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning-based system and method for content clustering and content threat assessment includes generating embedding values for each piece of content of corpora of content data; implementing unsupervised machine learning models that: receive model input comprising the embeddings values of each piece of content of the corpora of content data; and predict distinct clusters of content data based on the embeddings values of the corpora of content data; assessing the distinct clusters of content data; associating metadata with each piece of content defining a member in each of the distinct clusters of content data based on the assessment, wherein the associating the metadata includes attributing to each piece of content within the clusters of content data a classification label of one of digital abuse/digital fraud and not digital abuse/digital fraud; and identifying members or content clusters having digital fraud/digital abuse based on querying the distinct clusters of content data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.