301 citations · 341 across the 5 of their papers we have counts for
5 papers
Deep Uncertainty-Based Explore for Index Construction and Retrieval in Recommendation System
Xin Jiang, Kaiqiang Wang, Yinlong Wang +7
In recommendation systems, the relevance and novelty of the final results are selected through a cascade system of Matching -> Ranking -> Strategy. The matching model serves as the…
Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction
Huinan Sun, Guangliang Yu, Pengye Zhang +3
Click-through rate (CTR) prediction aims to predict the probability that the user will click an item, which has been one of the key tasks in online recommender and advertising syst…
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…
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
Han Zhu, Daqing Chang, Ziru Xu +6
Large-scale industrial recommender systems are usually confronted with computational problems due to the enormous corpus size. To retrieve and recommend the most relevant items to…
Learning Tree-based Deep Model for Recommender Systems
Han Zhu, Xiang Li, Pengye Zhang +4
Model-based methods for recommender systems have been studied extensively in recent years. In systems with large corpus, however, the calculation cost for the learnt model to predi…