Julie S. Weber

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We present a new algorithm for active learning embedded within an interactive calendar management system that learns its users' scheduling preferences. When the system receives a meeting request, the active learner selects a set of alternative solutions to present to the user; learning is then achieved by noting the user's preferences for the selected(More)
We are developing an adaptive reminding system that tailors its reminders to its users' reminding preferences through real-time interaction and feedback. To determine the potential utility of such a system, we conducted a multi-phase user study, presented in this paper, in which we evaluate people's preferences for the visual presentation of reminders.(More)
We describe a simulation system that models the user of a calendar-management tool. The tool is intended to learn the user's scheduling preferences, and we employ the simulator to evaluate learning strategies. The simulated user is instantiated with a set of preferences over local and global features of a schedule such as the level of importance of a(More)
We studied people's perception of and response to a set of visual and auditory notifications issued in a multi-task environment. Primary findings show that participants' reactive preference ratings of notifications delivered in various contexts during experimentation appear to contradict their reflective, overall ratings of the notification formats when(More)
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