Invention Application
- Patent Title: Predicting User Attentiveness to Electronic Notifications
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Application No.: US15139716Application Date: 2016-04-27
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Publication No.: US20170316320A1Publication Date: 2017-11-02
- Inventor: Hani Jamjoom , David M. Lubensky , Justin G. Manweiler , Katherine Vogt , Justin D. Weisz
- Applicant: international Business Machines Corporation
- Main IPC: G06N5/04
- IPC: G06N5/04 ; G06N99/00 ; G06N7/00

Abstract:
A database comprises historical information of a user's response to previous notifications. The database is accessed to determine a time at which to provide a (new) notification to the user, utilizing at least: a) current user activity status (e.g., determined from measurement information collected from one or more personal devices and/or user calendar events; b) time/day; and c) context information about the notification (e.g., geo-location, indoors/outdoors) including notification type (e.g., calendar entry, email, IM). The user gets the notification via a portable device at the determined time. A machine learning model can select the determined time by discriminating features of the previous notifications for which the user immediately attended versus those that were deferred and/or ignored. Content of the notification can also be altered in view of such discriminating features so as to increase a likelihood the user will immediately attend to the provided notification.
Public/Granted literature
- US10832160B2 Predicting user attentiveness to electronic notifications Public/Granted day:2020-11-10
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