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Found 4 papers, 3 papers with code
INFACT: An Online Human Evaluation Framework for Conversational Recommendation
Conversational recommender systems (CRS) are interactive agents that support their users in recommendation-related goals through multi-turn conversations.
INSPIRED2: An Improved Dataset for Sociable Conversational Recommendation
A recent example of such a dataset is INSPIRED, which consists of recommendation dialogs for sociable conversational recommendation, where items and entities were annotated using automatic keyword or pattern matching techniques.
Towards Retrieval-based Conversational Recommendation
One main challenge is that these generated responses both have to be appropriate for the given dialog context and must be grammatically and semantically correct.
A Survey on Conversational Recommender Systems
Recommender systems are software applications that help users to find items of interest in situations of information overload.
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