38 citations · 84 across the 12 of their papers we have counts for
12 papers
Sparse Attentive Memory Network for Click-through Rate Prediction with Long Sequences
Qianying Lin, Wen-Ji Zhou, Yanshi Wang +3
Sequential recommendation predicts users' next behaviors with their historical interactions. Recommending with longer sequences improves recommendation accuracy and increases the d…
A General Traffic Shaping Protocol in E-Commerce
Chenlin Shen, Guangda Huzhang, Yuhang Zhou +2
To approach different business objectives, online traffic shaping algorithms aim at improving exposures of a target set of items, such as boosting the growth of new commodities. Ge…
Imitate TheWorld: A Search Engine Simulation Platform
Yongqing Gao, Guangda Huzhang, Weijie Shen +4
Recent E-commerce applications benefit from the growth of deep learning techniques. However, we notice that many works attempt to maximize business objectives by closely matching o…
Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce
Xuesi Wang, Guangda Huzhang, Qianying Lin +1
Ensemble models in E-commerce combine predictions from multiple sub-models for ranking and revenue improvement. Industrial ensemble models are typically deep neural networks, follo…
Diversity Regularized Interests Modeling for Recommender Systems
Junmei Hao, Jingcheng Shi, Qing Da +4
With the rapid development of E-commerce and the increase in the quantity of items, users are presented with more items hence their interests broaden. It is increasingly difficult…
Delayed Feedback Modeling for the Entire Space Conversion Rate Prediction
Yanshi Wang, Jie Zhang, Qing Da +1
Estimating post-click conversion rate (CVR) accurately is crucial in E-commerce. However, CVR prediction usually suffers from three major challenges in practice: i) data sparsity:…