Learning and reasoning about interruption

2003/11/05 by Eric Horvitz, Johnson Apacible · 5 citations
Decision Sciences · Computer Science · #Personal Information Management and User Behavior #Data Visualization and Analytics #User Authentication and Security Systems

paper · doi:10.1145/958432.958440

openalex publication_date 2003/11/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

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.

Citations

• A Bayesian Approach to Learning Bayesian Networks with Local Structure

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• Eric Horvitz [wikipedia]