Preference elicitation for interface optimization

ABSTRACT

Decision-theoretic optimization is becoming a popular tool in the user interface community, but creating accurate cost (or utility) functions has become a bottleneck --- in most cases the numerous parameters of these functions are chosen manually, which is a tedious and error-prone process. This paper describes ARNAULD, a general interactive tool for eliciting user preferences concerning concrete outcomes and using this feedback to automatically learn a factored cost function. We empirically evaluate our machine learning algorithm and two automatic query generation approaches and report on an informal user study.

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Index Terms

• Human-centered computing

  • Human computer interaction (HCI)

• Software and its engineering

  • Software notations and tools

    • Development frameworks and environments

      • Integrated and visual development environments