A survey for trust-aware recommender systems: A deep learning perspective

A significant remaining challenge for existing recommender systems is that users may not trust recommender systems for either inaccurate recommendation or lack of explanation. Thus, it becomes critical to embrace a trustworthy recommender system. This survey provides a systematic summary of three categories of trust issues in recommender systems: social-aware recommender systems, which leverage users' social trust relationships; robust recommender systems, which filter untruthful information, noises and enhance attack resistance; and explainable recommender systems, which provide explanations of the recommended items. We focus on the work based on deep learning techniques, which is an emerging area in the recommendation research.(C) 2022 Elsevier B.V. All rights reserved.

Automated summary

This survey provides a systematic summary of three categories of trust issues in recommender systems and focuses on the work based on deep learning techniques.