Towards Generating Robust, Fair, and Emotion-Aware Explanations for Recommender Systems
Aug 20, 2022·
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1 min read
Bingbing Wen
Yichao Feng
Yongfeng Zhang
Chirag Shah
Abstract
We investigate how to generate explanations for recommender systems that are robust, fair, and sensitive to user emotions, proposing techniques to improve explanation quality along these dimensions.
Type
Publication
arXiv preprint
We explore methods for generating explanations in recommender systems that remain robust under perturbations, treat users fairly, and take emotional impact into account.
