27 citations · 29 across the 4 of their papers we have counts for
6 papers
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 Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search
Zhifang Fan, Dan Ou, Yulong Gu +7
Modeling user's historical feedback is essential for Click-Through Rate Prediction in personalized search and recommendation. Existing methods usually only model users' positive fe…
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search
Dian Cheng, Jiawei Chen, Wenjun Peng +5
A good personalized product search (PPS) system should not only focus on retrieving relevant products, but also consider user personalized preference. Recent work on PPS mainly ado…
Embedding-based Product Retrieval in Taobao Search
Sen Li, Fuyu Lv, Taiwei Jin +5
Nowadays, the product search service of e-commerce platforms has become a vital shopping channel in people's life. The retrieval phase of products determines the search system's qu…
Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling
Jia-Qi Yang, Xiang Li, Shuguang Han +4
Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner t…
Adversarial Multimodal Representation Learning for Click-Through Rate Prediction
Xiang Li, Chao Wang, Jiwei Tan +3
For better user experience and business effectiveness, Click-Through Rate (CTR) prediction has been one of the most important tasks in E-commerce. Although extensive CTR prediction…