Proactive notification of relevant feature suggestions based on contextual analysis
US11163617B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 24, 2018 |
| Grant date | Nov 2, 2021 |
| Priority date | — |
| Expiry date | Dec 17, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F3/04895
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to processing operations configured to tailor notifications of productivity feature suggestions based on predictive relevance to a context associate with user access to an electronic document. Machine learning modeling executes a contextual evaluation of user access to predictively determine relevance of a suggestion that relates to: 1) a confidence in the quality of the suggestion; and 2) a timing prediction as to the urgency for surfacing the suggestion to the user so that the suggestion is most applicable. Example notifications are proactive interruptions that aim to aid processing efficiency in task execution as well as an improve user interface experience when users work with an application/service and/or an application platform that comprises a suite of applications/services. A manner in which the notification is presented may vary based on the confidence in the relevance of the suggestion and timing relevance for interrupting a user's workflow.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.