Automated Fashion Size Normalization
This addresses the time-consuming manual process of size normalization for e-commerce platforms, though it appears incremental as it automates an existing task without a major breakthrough.
The authors tackled the problem of automating fashion size normalization to reduce e-commerce returns by mapping product sizes across brands to a common space using sales data, achieving results comparable to human-generated mappings.
The ability to accurately predict the fit of fashion items and recommend the correct size is key to reducing merchandise returns in e-commerce. A critical prerequisite of fit prediction is size normalization, the mapping of product sizes across brands to a common space in which sizes can be compared. At present, size normalization is usually a time-consuming manual process. We propose a method to automate size normalization through the use of salesdata. The size mappings generated from our automated approaches are comparable to human-generated mappings.