Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 51-60).

1. Introduction -- 1.1. Mobile notifications -- 1.2. Issues with mobile notifications -- 1.3. Solutions for interruptibility management

2. Interruptions -- 2.1. Definitions of interruptions from different research fields -- 2.2. Types of interruptions -- 2.3. Definition of interruptions in context of this lecture -- 2.4. Sources of interruptions

3. Cost of interruption -- 3.1. Impact on memory -- 3.2. Impact on ongoing task performance -- 3.3. Impact on users' emotional state -- 3.4. Impact on user experience -- 3.5. Individual differences in perceiving disruption from interruptions -- 3.6. Summary

4. An Overview of interruptibility management -- 4.1. Definition -- 4.2. Key dimensions for the design of interruptibility management systems

5. Interruptibility management in desktop environments -- 5.1. Interruptibility management by exploiting task-related information -- 5.2. Interruptibility management by using contextual data -- 5.3. Summary

6. Interruptibility management in mobile environments -- 6.1. Understanding users' perception toward interruptions caused by mobile notifications -- 6.2. Designing interruptibility management systems for delivering the right information at the right time -- 6.3. Designing interruptibility management systems for multi-device environments -- 6.4. Interruptibility management--an alternative approach for context-aware assistive apps -- 6.5. Summary

7. Limitations of the state of the art and open challenges -- 7.1. Deferring notifications -- 7.2. Monitoring cognitive context -- 7.3. Learning "good" behavior : interruptions for positive behavior intervention -- 7.4. Modeling for multiple devices -- 7.5. Need for large-scale studies -- 8. Summary.

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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 book presents an overview of the current state of the art in the area of intelligent notification mechanisms that rely on the awareness of users' context and preferences. 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.

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Title from PDF title page (viewed on January 26, 2020).