122 citations · 127 across the 3 of their papers we have counts for
3 papers
cs.LG2022
Learning Large-scale Universal User Representation with Sparse Mixture of Experts
Caigao Jiang, Siqiao Xue, James Zhang +3
Learning user sequence behaviour embedding is very sophisticated and challenging due to the complicated feature interactions over time and high dimensions of user features. Recent…
cs.LG2021★ 5 cited
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data
Zhibo Zhu, Ziqi Liu, Ge Jin +4
Time series forecasting is widely used in business intelligence, e.g., forecast stock market price, sales, and help the analysis of data trend. Most time series of interest are mac…
cs.IR2018★ 122 cited
Attentive Aspect Modeling for Review-aware Recommendation
Xinyu Guan, Zhiyong Cheng, Xiangnan He +4
In recent years, many studies extract aspects from user reviews and integrate them with ratings for improving the recommendation performance. The common aspects mentioned in a user…