“Fixing the curse of the bad product descriptions” – Search-boosted tag recommendation for E-commerce products

摘要

•We perform a study on the tagging behavior of sellers in an e-commerce platform.•We design new tag quality attributes that exploit the collective behavior of users.•Our attributes exploit the synergy between search and quality of textual content.•Queries and clicks can offer useful data for recommending quality tags for products.•Our best method, a deep L2R framework, greatly outperforms state-of-the-art methods.