Automatic construction of personalized customer interfaces

Interface personalization can improve a user's performance and subjective impression of interface quality and responsiveness. Personalization is difficult to implement as it requires an accurate model of a user's intentions and a formal model of how an interface meets a user's need. We present a novel model for tractable inference of consumer intentions in the context of grocery shopping. The model makes unique use of a priori temporal relations to simplify inference. We then present a simple interface generation framework that was inspired by viewing user interface interaction as a channel coding problem. The resulting model defines a simplified but clear notion of a user's utility for an interface. We demonstrate the effectiveness of the research prototype on some simple data, and explain how the model can be augmented with richer user modeling to create a deployable application.