Learning and Reasoning about Interruption

Eric Horvitz and Johnson Apacible

Adaptive Systems and Interaction
Microsoft Research
Redmond, Washington 98052

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We present methods for inferring the cost of interrupting users based on multiple streams of events including information generated by interactions with computing devices, visual and acoustical analyses, and data drawn from online calendars. Following a review of prior work on techniques for deliberating about the cost of interruption associated with notifications, we introduce methods for learning models from data that can be used to compute the expected cost of interruption for a user. We describe the Interruption Workbench, a set of event-capture and modeling tools. Finally, we review experiments that characterize the accuracy of the models for predicting interruption cost and discuss research directions.

Keywords: Attentional User Interfaces, AUI, augmented cognition, interruptability, user modeling, models of attention, human-computer interface, probability, decision theory, alerting, notifications, interruptions, attentive user interface.

In: E. Horvitz and J. Apacible. Learning and Reasoning about Interruption, Proceedings of ICMI 2003, ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, Canada.

Author Email: horvitz@microsoft.com

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