This workshop is positioned as a forum to present and discuss novel research directions in interactive and conversational recommender systems as well as constituent AI technologies that represent the next generation of recommender systems and personalized, conversational assistants.
Historical work on recommender systems focused on interactive and conversational aspects as evidenced by the large literature on critiquing-based interaction dating back to the 1990’s. With the dawn of the Netflix Challenge, a sizable fraction of recommendation research shifted away from interaction and conversation and focused more on formal machine learning aspects of training objectives and optimization on offline data. However, recent years have seen an increase in work in interactive, sequential (e.g., session-based) interactions with recommender systems. Furthermore, the rise of Conversational AI-based assistants in the form of Apple’s Siri, Amazon’s Alexa, and the Google Assistant have re-invigorated interest in dialog-based sequential interaction, with a limited degree of personalization.
Encouraged by this recent interest in interactive and conversational recommender systems, the workshop aspires to bring together AI researchers from recommender systems, machine and reinforcement learning, dialog systems, natural language processing, human computer interaction, psychology and econometrics for a day of research presentations and open discussion about the future of this high impact and highly cross-disciplinary research area.
Workshop topics:
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Topics include (but are not limited to):
* Goal-directed and Personalized Conversational AI
* Critiquing-based Recommendation Systems
* Reinforcement Learning in Multi-turn Interactions
* User Privacy and Security
* Multimodal Context and Situation-aware Modeling
* Preference Elicitation and Preference Construction
* Recommendation with Complex Preferences
* Explanations and Endorsements in Recommendation
* Human-Computer Interaction in Recommendation
* Grounding Dialog in Preferences and Constraints
* Natural Language Expression of Preferences
* Expressing Preferences over Latent Embeddings
* Simulation Environments and Benchmark Datasets
* Evaluation and Metrics
* User Choice Modeling
* Theory of Mind and Mental Model Representations
Important Dates:
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* Paper submission: November 15, 2019
* Notifications of acceptance: December 4, 2019
* Camera-ready due: December 21, 2019
* Workshop date: February 7th or 8th, 2020 (one day)
Submission Procedure:
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We welcome previously unsubmitted work, papers submitted to the main AAAI conference, and papers reporting research already published provided they align well with the workshop topic.
Three types of submissions are solicited:
- Full-length papers (up to 7 pages + 1 page for references in AAAI format)
- Challenge or position papers (2 pages + 1 page for references in AAAI format)
- Already published papers (1 page: an abstract in AAAI format with a link to the full paper)
Paper Submissions should be made through the workshop EasyChair web site