IAI MovieBot: A Conversational Movie Recommender System
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Sep 2020.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 2.
4 papers.
- 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
- 2021Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systemscited by 10
- 2023Talk the Walk: Synthetic Data Generation for Conversational Music Recommendationcited by 9
- 2023Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Datasetcited by 6
- 2023Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset13 Mar 2023
- 2023Talk the Walk: Synthetic Data Generation for Conversational Music Recommendation27 Jan 2023
- 2021Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systems26 Nov 2021
- 2021Advances and Challenges in Conversational Recommender Systems: A Survey23 Jan 2021