197 citations · 620 across the 19 of their papers we have counts for
30 papers
From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba
Xinyuan Qi, Kai Hou, Tong Liu +3
Time series forecasting (TSF) is fundamentally required in many real-world applications, such as electricity consumption planning and sales forecasting. In e-commerce, accurate tim…
End-to-End User Behavior Retrieval in Click-Through RatePrediction Model
Qiwei Chen, Changhua Pei, Shanshan Lv +3
Click-Through Rate (CTR) prediction is one of the core tasks in recommender systems (RS). It predicts a personalized click probability for each user-item pair. Recently, researcher…
GRN: Generative Rerank Network for Context-wise Recommendation
Yufei Feng, Binbin Hu, Yu Gong +3
Reranking is attracting incremental attention in the recommender systems, which rearranges the input ranking list into the final rank-ing list to better meet user demands. Most exi…
Revisit Recommender System in the Permutation Prospective
Yufei Feng, Yu Gong, Fei Sun +2
Recommender systems (RS) work effective at alleviating information overload and matching user interests in various web-scale applications. Most RS retrieve the user's favorite cand…
Explore User Neighborhood for Real-time E-commerce Recommendation
Xu Xie, Fei Sun, Xiaoyong Yang +4
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been wid…
Towards Long-term Fairness in Recommendation
Yingqiang Ge, Shuchang Liu, Ruoyuan Gao +8
As Recommender Systems (RS) influence more and more people in their daily life, the issue of fairness in recommendation is becoming more and more important. Most of the prior appro…