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.
Cite
@article{arxiv.1908.09980,
title = {Automated Fashion Size Normalization},
author = {Eddie S. J. Du and Chang Liu and David H. Wayne},
journal= {arXiv preprint arXiv:1908.09980},
year = {2019}
}