2 code implementations • KDD 2018 • Jizhe Wang, Pipei Huang, Huan Zhao, Zhibo Zhang, Binqiang Zhao, Dik Lun Lee
Using online A/B test, we show that the online Click-Through-Rate (CTRs) are improved comparing to the previous recommendation methods widely used in Taobao, further demonstrating the effectiveness and feasibility of our proposed methods in Taobao's live production environment.
no code implementations • 24 May 2018 • Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang
The deep cascade structure and the combination rule enable the proposed \textit{ldcTree} to have a stronger distributed feature representation ability.
5 code implementations • 17 Apr 2019 • Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.
Ranked #1 on Information Retrieval on Amazon
1 code implementation • 6 May 2019 • Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao
In particular, there exist two requirements for fashion outfit recommendation: the Compatibility of the generated fashion outfits, and the Personalization in the recommendation process.
9 code implementations • 15 May 2019 • Qiwei Chen, Huan Zhao, Wei Li, Pipei Huang, Wenwu Ou
Deep learning based methods have been widely used in industrial recommendation systems (RSs).
Ranked #9 on Recommendation Systems on MovieLens 1M