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.