| dc.description.abstract | In this project we developed a skill for recommending points of interest through conver-
sations with users, suitable for a digital assistant stationed at a public venue. The skill
was part of a larger effort involving several teams working on a conversational conference
assistant called DAGFiNN, which was exhibited at the 2022 European Conference on
Information Retrieval (ECIR). The assistant was developed on the open-source conver-
sational AI platform called Rasa and implemented on a social robot made by Furhat
Robotics alongside an external display. Our skill focuses on sequential recommendations
through slot-filling, and allows for related follow-up questions along the way, such as
asking for transport or walking distance to the recommended POI. Rich responses shown
on the display includes subtitles for the dialogue, locations on a map, QR-codes for links,
and other useful information. The skill was also made to be easily re-adaptable for other
public events, by changing only the database and a few values in the source code.
Results suggested that the skill was successful in providing effective and accurate recom-
mendations based the user’s preference, but that lack of system-initiated guidance could
leave the user confused about its scope. | |