Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges
It addresses the issue of disruptive notifications for users in real-time systems, but is incremental as it synthesizes existing research rather than presenting new findings.
This survey tackles the problem of notifications disrupting users by reviewing intelligent mechanisms that learn user behavior to optimize timing and context for information delivery, aiming to maximize receptivity.
Notifications provide a unique mechanism for increasing the effectiveness of real-time information delivery systems. However, notifications that demand users' attention at inopportune moments are more likely to have adverse effects and might become a cause of potential disruption rather than proving beneficial to users. In order to address these challenges a variety of intelligent notification mechanisms based on monitoring and learning users' behavior have been proposed. The goal of such mechanisms is maximizing users' receptivity to the delivered information by automatically inferring the right time and the right context for sending a certain type of information. This article provides an overview of the current state of the art in the area of intelligent notification mechanisms that relies on the awareness of users' context and preferences. More specifically, we first present a survey of studies focusing on understanding and modeling users' interruptibility and receptivity to notifications from desktops and mobile devices. Then, we discuss the existing challenges and opportunities in developing mechanisms for intelligent notification systems in a variety of application scenarios.