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

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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.

论文关键词:Tag recommendation,Search,E-commerce,E-marketplace,Deep learning

论文评审过程:Author links open overlay panelFabiano M.BelémPersonaEnvelopeRodrigo M.SilvaaClaudio M.V.de AndradeaGabrielPersonaFelipeMingoteaRaphaelBalletbHeltonAlpontibHenrique P.de OliveirabJussara M.AlmeidaaMarcos A.Gonçalvesa

论文官网地址:https://doi.org/10.1016/j.ipm.2020.102289