Conversational recommender systems support users in accomplishing recommendation-related goals via multi-turn conversations. To better model dynamically changing user preferences and provide the community with a reusable development framework, we introduce IAI MovieBot, a conversational recommender system for movies. It features a task-specific dialogue flow, a multi-modal chat interface, and an effective way to deal with dynamically changing user preferences. The system is made available open source and is operated as a channel on Telegram.
@article{arxiv.2009.03668,
title = {IAI MovieBot: A Conversational Movie Recommender System},
author = {Javeria Habib and Shuo Zhang and Krisztian Balog},
journal= {arXiv preprint arXiv:2009.03668},
year = {2020}
}
Comments
Proceedings of the 29th ACM International Conference on Information and Knowledge Management, Oct 2020