Explainable recommendation attempts to develop models that generate not only high-quality recommendations but also intuitive explanations. It tries to address the problem of why: by providing explanations to users or system designers, it helps humans to understand why certain items are recommended by the algorithm, where the human can either be users or system designers. Explainable recommendation helps to improve the transparency, persuasiveness,...