Date of Original Version
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-21726-5_11
Abstract or Description
We contribute a method for approximating users’ interruptibility costs to use for experience sampling and validate the method in an application that learns when to automatically turn off and on the phone volume to avoid embarrassing phone interruptions. We demonstrate that users have varying costs associated with interruptions which indicates the need for personalized cost approximations. We compare different experience sampling techniques to learn users’ volume preferences and show those that ask when our cost approximation is low reduce the number of embarrassing interruptions and result in more accurate volume classifiers when deployed for long-term use.
Lecture Notes in Computer Science, 6696, 170-187.