Hybrid human machine learning system and method
US9471883B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 9, 2014 |
| Grant date | Oct 18, 2016 |
| Priority date | — |
| Expiry date | Mar 16, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/93
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention provide a system, method, and article of hybrid human machine learning system with tagging and scoring techniques for sentiment magnitude scoring of textual passages. The combination of machine learning systems with data from human pooled language extraction techniques enable the present system to achieve high accuracy of human sentiment measurement and textual categorization of raw text, blog posts, and social media streams. This information can then be aggregated to provide brand and product strength analysis. A data processing module is configured to get streaming data and then tag the streaming data automatically using the machine learning output. A crowdsourcing module is configured to select a subset of social media posts that have been previously stored in the database, and present the social media posts on the web, which then tags each social media with a selected set of attributes. A score aggregator module configured to provide a score based on a user's feedback for each social media post.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.