Machine-based learning for automatically categorizing data on per-user basis
US8682819B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 19, 2008 |
| Grant date | Mar 25, 2014 |
| Priority date | — |
| Expiry date | Jan 26, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Architecture that employs machine-based learning to automatically categorize data on a per-user basis. Auto-tagging reduces the burden on infoworkers by creating a machine learning model to learn from user tagging behavior or preferences. Once this information is obtained, a trained model for this specific user is used to assign tags to incoming data, such as emails. The architecture finds particular applicability to compliance and message retention policies that otherwise would mandate extra work for the infoworker. The architecture learns the tagging behavior of a user and uses this learned behavior to automatically tag data based on the user's prior tagging habits. A regression algorithm is employed to process the training data according to an n-dimensional framework for prediction and application of the tag(s) to the incoming messages.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.