IAI MovieBot: A Conversational Movie Recommender System
arXiv:2009.03668 · doi:10.1145/3340531.3417433
Abstract
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.
Proceedings of the 29th ACM International Conference on Information and Knowledge Management, Oct 2020
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- Analyzing and Simulating User Utterance Reformulation in Conversational Recommender Systems
- Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset
- DAGFiNN: A Conversational Conference Assistant
- Identifying Breakdowns in Conversational Recommender Systems using User Simulation
- Leveraging User Simulation to Develop and Evaluate Conversational Information Access Agents
- IAI MovieBot 2.0: An Enhanced Research Platform with Trainable Neural Components and Transparent User Modeling