Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences
Filip Radlinski, Krisztian Balog, Bill Byrne, K. S. Krishnamoorthi · 2019
Conversational recommendation has recently attracted significant attention.As systems must understand users' preferences, training them has called for conversational corpora, typically derived from task-oriented conversations.We observe that such corpora often do not reflect how people naturally describe preferences.We present a new approach to obtaining user preferences in dialogue: Coached Conversational Preference Elicitation.It allows collection of natural yet structured conversational preferences.Studying the dialogues in one domain, we present a brief quantitative analysis of how people describe movie preferences at scale.Demonstrating the methodology, we release the CCPE-M dataset to the community with over 500 movie preference dialogues expressing over 10,000 preferences.1