Using a networked infrastructure of easily available sensors and context-processing components, we are developing applications for the support of workplace interactions. Notions o...
We propose a design model for guiding learning in exploratory environments through representational choices. Selecting the appropriate representations at the correct granularity ca...
Katherine Howland, Benedict du Boulay, Judith Good
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...