Automatic construction of personalized customer interfaces

ABSTRACT

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.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)

Additional Classification:
  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS

General Terms:
Algorithms, Human Factors

Keywords:
e-commerce, interface cost models, interface personalization, online grocery shopping, particle filters, temporal demand models