This paper presents a context-aware mobile recommender system, codenamed Magitti. Magitti is unique in that it infers user activity from context and patterns of user behavior and,...
Victoria Bellotti, James Bo Begole, Ed Huai-hsin C...
It is well-established finding that people find maps easier to use when they are aligned so that "up" on the map corresponds to the user's forward direction. With m...
Domestic ubiquitous computing systems often rely on inferences about activities in the home, but the open-ended, dynamic and heterogeneous nature of the home poses serious problem...
William W. Gaver, Phoebe Sengers, Tobie Kerridge, ...
We present a machine-learned model that can automatically detect when a student using an intelligent tutoring system is off-task, i.e., engaged in behavior which does not involve ...
The increasing integration of education and technology has led to the development of a range of note-taking applications. Our project's goal is to provide empirical data to g...