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Published on Aug 30, 2010
Presented at DIS 2010 Joshua Hailpern, Nicholas Jitkoff, Joseph Subida, and Karrie Karahalios
When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying high-utility applica- tions is a critical first step for Task Analysis, Time Management/Workflow analysis, and Interruption research. However, existing techniques fail to identify at least 57% of these applications. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility without identifying task. In this paper, we present an objective util- ity function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. This model of computer usage is based upon 321 hours of real-world data from 22 users (both pro- fessional and academic). Unlike existing approaches, our model is not limited by a pre-existing set of applications or known tasks. We conclude with a discussion of the direct implications for improving accuracy in the fields of inter- ruptions, task analysis, and time management systems.