Rethinking Conversational Recommendations
A S M Ahsan-Ul Haque, Hongning Wang · Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 2022
Conversational recommender systems (CRS) dynamically obtain the users' preferences via multi-turn questions and answers. The existing CRS solutions are widely dominated by deep reinforcement learning algorithms. However, deep reinforcement learning methods are often criticized for lacking interpretability and requiring a large amount of training data to perform.