Constructing and Evaluating Sensor-Based Statistical Models of Human Interruptibility

Опубликовано 6 сентября 2016, 6:16

While people can typically make a rapid assessment of another person’s interruptibility, current systems generally have no way to consider whether an interruption is appropriate.  Current systems therefore tend to interrupt at inappropriate times or unduly demand attention.  I will present my work examining the feasibility and robustness of sensor-based statistical models of human interruptibility.  I have conducted a series of studies to explore the utility of a number of potential sensors, examine human ability to estimate interruptibility, deploy and evaluate actual sensors in office work environments, and develop models of task engagement based on low-level event streams.  My studies show that a typical laptop computer, with no additional sensors, can support models that identify Highly