In order to adapt to the expansion and transformation of the garment customization, big data is increasingly used in the online customization process. The aim of our research was to propose a method of tailoring clothing throughout the early stages of personal design and product development. This approach improves the understanding of garment fitting by analyzing individual preferences, and also helps designers capture user needs more quickly and deal with them more accurately. Our approach is built upon garment customization using unsupervised approach to learning visual compatibility from clothing data sets. For the garment definition, a competitive analysis was made to identify garment custom process. Then, training model was applied in personal customization environment while examining the links through machine learning module. Indeed, garment customization with big data provides new insights into garment customization, in terms of effectively optimizing the combination of mix-and-match clothing choices as well as generative learning of fashion design.

中文翻译：

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服装定制大数据——优化设计中的处理与分析

为适应服装定制的扩张和转型，在线定制过程中越来越多地使用大数据。我们研究的目的是提出一种在个人设计和产品开发的早期阶段剪裁服装的方法。这种方法通过分析个人喜好提高了对服装合身的理解，也帮助设计师更快地捕捉用户需求并更准确地处理它们。我们的方法建立在服装定制的基础上，使用无监督的方法从服装数据集中学习视觉兼容性。对于服装定义，进行了竞争分析以确定服装定制流程。然后，将训练模型应用于个人定制环境，同时通过机器学习模块检查链接。确实，