Department of Computer Science
Adaptive tradeoff explanations in conversational recommenders
The completeness and certainty of a user's preferences may vary during her preference construction process in a conversational recommender. In order to more effectively support users to uncover their hidden criteria and/or solve preference conflicts, we propose to generate adaptive tradeoff explanations in organization-based recommender interfaces, to be conditional on the user's contextual needs. An experiment shows the adaptive element's higher potential to improve recommendation efficiency, relative to methods without this feature. Copyright 2009 ACM.
Conversational recommenders, Explanation, Preference elicitation
Source Publication Title
RecSys '09 Proceedings of the third ACM conference on Recommender systems
New York, United States
Chen, Li. "Adaptive tradeoff explanations in conversational recommenders." RecSys '09 Proceedings of the third ACM conference on Recommender systems (2009): 225-228.