C
Chao Li
Researcher at Alibaba Group
Publications - 4
Citations - 485
Chao Li is an academic researcher from Alibaba Group. The author has contributed to research in topics: Personalization & Recommender system. The author has an hindex of 4, co-authored 4 publications receiving 179 citations.
Papers
More filters
Posted Content
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Chao Li,Zhiyuan Liu,Mengmeng Wu,Yuchi Xu,Pipei Huang,Huan Zhao,Guoliang Kang,Qiwei Chen,Wei Li,Dik Lun Lee +9 more
TL;DR: This paper designs a multi-interest extractor layer based on the recently proposed dynamic routing mechanism, which is applicable for modeling and extracting diverse interests from user's behaviors, and proposes a technique named label-aware attention to help the learning process of user representations.
Proceedings ArticleDOI
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Chao Li,Zhiyuan Liu,Mengmeng Wu,Yuchi Xu,Huan Zhao,Pipei Huang,Guoliang Kang,Qiwei Chen,Wei Li,Dik Lun Lee +9 more
TL;DR: In this article, a multi-interest extractor layer based on the recently proposed dynamic routing mechanism is proposed for modeling and extracting diverse interests from user's behaviors, and a technique named label-aware attention is proposed to help the learning process of user representations.
Proceedings ArticleDOI
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
Wen Chen,Pipei Huang,Jiaming Xu,Xin Guo,Cheng Guo,Fei Sun,Chao Li,Andreas Pfadler,Huan Zhao,Binqiang Zhao +9 more
TL;DR: Wang et al. as discussed by the authors proposed a Personalized Outfit Generation (POG) model, which connects user preferences regarding individual items and outfits with Transformer architecture, and deployed POG on a platform named Dida in Alibaba to generate personalized outfits for the users of the online application iFashion.
Posted Content
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
Wen Chen,Pipei Huang,Jiaming Xu,Xin Guo,Cheng Guo,Fei Sun,Chao Li,Andreas Pfadler,Huan Zhao,Binqiang Zhao +9 more
TL;DR: This paper proposes a Personalized Outfit Generation (POG) model, which connects user preferences regarding individual items and outfits with Transformer architecture, and releases a large-scale dataset, which is the largest, publicly available, fashion related dataset, and the first to provide user behaviors relating to both outfits and fashion items.