When people talk about fashion, they care about the underlying meaning of fashion concepts,e.g., style.For example, people ask questions like what features make this dress smart.However, the product descriptions in today fashion websites are full of domain specific and low level words. It is not clear to people how exactly those low level descriptions can contribute to a style or any high level fashion concept. In this paper, we proposed a data driven solution to address this concept understanding issues by leveraging a large number of existing product data on fashion sites. We first collected and categorized 1546 fashion keywords into 5 different fashion categories. Then, we collected a new fashion product dataset with 853,056 products in total. Finally, we trained a deep learning model that can explicitly predict and explain high level fashion concepts in a product image with its low level and domain specific fashion features.

中文翻译：

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AI可以为你解密时尚行话吗？

当人们谈论时尚时，他们关心时尚概念的潜在含义，例如风格。例如，人们会问诸如什么功能使这件衣服变得聪明之类的问题。但是，当今时尚网站上的产品描述充满了特定领域和低级水平词。人们不清楚这些低层次的描述究竟如何对风格或任何高级时尚概念做出贡献。在本文中，我们提出了一种数据驱动的解决方案，通过利用时尚网站上的大量现有产品数据来解决这一概念理解问题。我们首先收集并分类了 1546 个时尚关键词，分为 5 个不同的时尚类别。然后，我们收集了一个新的时尚产品数据集，总共有 853,056 种产品。最后，