Adaptive tradeoff explanations in conversational recommenders.
RECSYS(2009)
摘要
ABSTRACTThe 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.
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