Identifying spammer profiles
US11089048B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 27, 2018 |
| Grant date | Aug 10, 2021 |
| Priority date | — |
| Expiry date | Aug 13, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1425
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A spammer profile detector uses multi-stage machine learning approach, where a content-based machine learning model, a connection graph machine learning model, and a behavior-based machine learning model are used sequentially, each model generating a score indicating the likelihood that a profile is a spammer profile. The content-based machine learning model examines and evaluates information stored in a member profile. The connection graph machine learning model examines and evaluates a member's connections. The behavior-based machine learning model examines and evaluates activities of a member represented by a member profile. The score produced by the spammer profile detector can be used to determine whether the profile should be flagged as a spammer profile, whether the profile should be omitted when determining a count of the total number of active member profiles within the system, whether the profile should be restricted or removed from the system, etc.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.