11 citations · 15 across the 5 of their papers we have counts for
5 papers
Graph Contrastive Learning with Multi-Objective for Personalized Product Retrieval in Taobao Search
Longbin Li, Chao Zhang, Sen Li +3
In e-commerce search, personalized retrieval is a crucial technique for improving user shopping experience. Recent works in this domain have achieved significant improvements by th…
Rethinking the Role of Pre-ranking in Large-scale E-Commerce Searching System
Zhixuan Zhang, Yuheng Huang, Dan Ou +4
E-commerce search systems such as Taobao Search, the largest e-commerce searching system in China, aim at providing users with the most preferred items (e.g., products). Due to the…
MAKE: Vision-Language Pre-training based Product Retrieval in Taobao Search
Xiaoyang Zheng, Zilong Wang, Ke Xu +4
Taobao Search consists of two phases: the retrieval phase and the ranking phase. Given a user query, the retrieval phase returns a subset of candidate products for the following ra…
Multi-Objective Personalized Product Retrieval in Taobao Search
Yukun Zheng, Jiang Bian, Guanghao Meng +7
In large-scale e-commerce platforms like Taobao, it is a big challenge to retrieve products that satisfy users from billions of candidates. This has been a common concern of academ…
Modeling User Behavior with Graph Convolution for Personalized Product Search
Fan Lu, Qimai Li, Bo Liu +7
User preference modeling is a vital yet challenging problem in personalized product search. In recent years, latent space based methods have achieved state-of-the-art performance b…