Notification filtering using machine learning models

Abstract

Approaches of the disclosure are directed towards the intelligent management of notifications. Notifications can be intelligently managed across digital devices by contextualizing and prioritizing notifications to, for example, match a current state or situation of a user. Incoming notifications may be contextualized by analyzing their content and sources, such as by using large language models. Such an approach may further take into account the user's current status, including factors such as location, activity, and personal preferences, as may be obtained from various sources or learned over time. Preferences or appropriate delivery methods can be learned by observing and/or analyzing user interactions associated with previously-presented notifications and adjusting the delivery methods for subsequent notifications, which may involve suppressing the notification, presenting immediately, changing an alert type, or altering content for presentation.