The paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’ sustainability, and explainable model assessment. The paper describes practical problem explanations, methodologies, and published datasets that may serve as an inspiration for further research. The proposed structure of the survey organizes knowledge in the fashion recommendation domain and will be beneficial for those who want to learn the topic from scratch, expand their knowledge, or find a new field for research. Furthermore, the information included in this paper could contribute to developing an effective and ethical fashion-based recommendation system.

本文回顾了时尚兼容性推荐领域中使用的方法。我们根据可重复性、可解释性和新颖性来选择方法，然后按时间顺序和主题进行组织。我们提出了与时尚兼容性推荐任务相关的公开数据集的一般特征。最后，我们分析了数据集的表征偏差、基于时尚的算法的可持续性以及可解释的模型评估。该论文描述了实际问题的解释、方法论和已发布的数据集，这些可以为进一步研究提供灵感。拟议的调查结构组织了时尚推荐领域的知识，对于那些想要从头开始学习该主题、扩展知识或寻找新研究领域的人来说将是有益的。此外，本文中包含的信息有助于开发有效且符合道德的时尚推荐系统。