213 citations · 360 across the 8 of their papers we have counts for
10 papers
Truncation-Free Matching System for Display Advertising at Alibaba
Jin Li, Jie Liu, Shangzhou Li +8
Matching module plays a critical role in display advertising systems. Without query from user, it is challenging for system to match user traffic and ads suitably. System packs up…
COLD: Towards the Next Generation of Pre-Ranking System
Zhe Wang, Liqin Zhao, Biye Jiang +3
Multi-stage cascade architecture exists widely in many industrial systems such as recommender systems and online advertising, which often consists of sequential modules including m…
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
Pi Qi, Xiaoqiang Zhu, Guorui Zhou +5
Rich user behavior data has been proven to be of great value for click-through rate prediction tasks, especially in industrial applications such as recommender systems and online a…
DCAF: A Dynamic Computation Allocation Framework for Online Serving System
Biye Jiang, Pengye Zhang, Rihan Chen +7
Modern large-scale systems such as recommender system and online advertising system are built upon computation-intensive infrastructure. The typical objective in these applications…
A Deep Recurrent Survival Model for Unbiased Ranking
Jiarui Jin, Yuchen Fang, Weinan Zhang +7
Position bias is a critical problem in information retrieval when dealing with implicit yet biased user feedback data. Unbiased ranking methods typically rely on causality models a…
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling
Guorui Zhou, Kailun Wu, Weijie Bian +3
Recently, click-through rate (CTR) prediction models have evolved from shallow methods to deep neural networks. Most deep CTR models follow an Embedding\&MLP paradigm, that is, fir…