RingLearn: Long-term mitigation of disruptive smartphone interruptions

Mitigating the consequences of disruptive smartphone interruptions remains a challenging problem for smartphone designers. Proposed solutions often incorporate machine-learning techniques with remedies that include delaying user notifications until an opportune moment or changing the intensity and/or mode of the notification (fewer rings, vibration mode). This paper describes a new machine-learning approach that aims to maintain the quality of mitigation under concept drift - unforeseen changes in context or the user´s behaviour over time. We demonstrate our approach by developing an application for Android phones to mitigate disruptive phone calls (RingLearn). We report on a field trial of the application conducted over 2 months with 10 users and suggest that long-term mitigation can be practical with careful design that addresses concept drift.