Intensional Summaries as Cooperative Responses in Dialogue: Automation and Evaluation


Despite its long history, and a great deal of research producing many useful algorithms and observations, research in cooperative response generation has had little impact on the recent commercialization of dialogue technologies, particularly within the spoken dialogue community. We hypothesize that a particular type of cooperative response, intensional summaries, are
effective for when users are unfamiliar with the domain. We evaluate this hypothesis with two experiments with cruiser, a DS for in-car or mobile users to access restaurant information. First, we compare cruiser with a baseline system-initiative DS, and show that users prefer cruiser. Then, we experiment with four algorithms for constructing intensional summaries in cruiser, and show that two summary types are equally effective: summaries that maximize domain coverage and summaries that maximize utility with respect to a user model.

