Do You Have any Recommendation? An Annotation System for the Seekers’ Strategies in Recommendation Dialogues

The development of dialogue systems benefits from the study of the communication strategies used by human speakers. In the context of recommendation dialogue systems some researchers have investigated the sociable recommendation strategies employed by the Recommenders in natural settings to make successful and persuasive recommendations (Hayati et al. 2020 INSPIRED corpus). However, the Seeker’s contribution, as well as the Recommender’s, shapes the development of the communicative exchange, in that the Seekers may use specific strategies to disclose their preferences and reach their goal. So, modelling the Seeker’s communicative strategies along with the ones used by the Recommender may improve the efficiency of recommendation dialogue systems. In this work, we provide a reliable tagset for the Seekers utterances present in the Inspired dataset, defining a set of communicative strategies coherent with the already existing one for the Recommenders.