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 a user values as high-utility applications. Identifying high-utility applications 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. We present an objective utility 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 professional and academic). Unlike existing approaches, our model is not limited to 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 interruptions, task analysis, and time management systems.

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 applications 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 utility 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 professional 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 interruptions, task analysis, and time management systems.

GatherReader is a prototype e-reader with both pen and multi-touch input that illustrates several interesting design trade-offs to fluidly interleave content consumption behaviors (reading and flipping through pages) with information gathering and informal organization activities geared to active reading tasks. These choices include (1) relaxed precision for casual specification of scope; (2) multiple object collection via a visual clipboard; (3) flexible workflow via deferred action; and (4) complementary use of pen+touch. Our design affords active reading by limiting the transaction costs for secondary subtasks, while keeping users in the flow of the primary task of reading itself. Author Keywords active reading; informal interaction; pen; touch; tablets.