  Providing system-generated explanations for recommendations represents an
important step towards transparent and trustworthy recommender systems.
Explainable recommender systems provide a human-understandable rationale for
their outputs. Over the last two decades, explainable recommendation has
attracted much attention in the recommender systems research community. This
paper aims to provide a comprehensive review of research efforts on visual
explanation in recommender systems. More concretely, we systematically review
the literature on explanations in recommender systems based on four dimensions,
namely explanation goal, explanation scope, explanation style, and explanation
format. Recognizing the importance of visualization, we approach the
recommender system literature from the angle of explanatory visualizations,
that is using visualizations as a display style of explanation. As a result, we
derive a set of guidelines that might be constructive for designing explanatory
visualizations in recommender systems and identify perspectives for future work
in this field. The aim of this review is to help recommendation researchers and
practitioners better understand the potential of visually explainable
recommendation research and to support them in the systematic design of visual
explanations in current and future recommender systems.
