Method and system for semi-supervised semantic task management from semi-structured heterogeneous data streams
US11210613B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 25, 2017 |
| Grant date | Dec 28, 2021 |
| Priority date | — |
| Expiry date | Dec 31, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention are directed to a computer-implemented machine-learning method and system for automatically creating and updating tasks by reading signals from external data sources and understanding what users are doing. Embodiments of the present invention are directed to a computer-implemented machine-learning method and system for automatically completing tasks by reading signals from external sources and understanding when an existing task has been executed. Tasks created are representable and explainable in a human readable format that can be shown to users and used to automatically fill productivity applications including but not limited to task managers, to-do lists, project management, time trackers, and daily planners. Tasks created are representable in a way that can be interpreted by a machine such as a computer system or an artificial intelligence so that external systems can be delegated or connected to the system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.