activity
20182024
most citedNPA: Neural News Recommendation with Personalized Attention

315 citations · 629 across the 28 of their papers we have counts for

collaborators
Showing cs.IRShow all

20 papers · 1 filter

cs.IR2023

Contrastive Multi-view Framework for Customer Lifetime Value Prediction

Chuhan Wu, Jingjie Li, Qinglin Jia +3

Accurate customer lifetime value (LTV) prediction can help service providers optimize their marketing policies in customer-centric applications. However, the heavy sparsity of cons…

cs.IR20221 cited

FUM: Fine-grained and Fast User Modeling for News Recommendation

Tao Qi, Fangzhao Wu, Chuhan Wu +1

User modeling is important for news recommendation. Existing methods usually first encode user's clicked news into news embeddings independently and then aggregate them into user e…

cs.IR2022

News Recommendation with Candidate-aware User Modeling

Tao Qi, Fangzhao Wu, Chuhan Wu +1

News recommendation aims to match news with personalized user interest. Existing methods for news recommendation usually model user interest from historical clicked news without th…

cs.IR20224 cited

ProFairRec: Provider Fairness-aware News Recommendation

Tao Qi, Fangzhao Wu, Chuhan Wu +5

News recommendation aims to help online news platform users find their preferred news articles. Existing news recommendation methods usually learn models from historical user behav…

cs.IR20223 cited

FairRank: Fairness-aware Single-tower Ranking Framework for News Recommendation

Chuhan Wu, Fangzhao Wu, Tao Qi +1

Single-tower models are widely used in the ranking stage of news recommendation to accurately rank candidate news according to their fine-grained relatedness with user interest ind…

cs.IR20227 cited

End-to-end Learnable Diversity-aware News Recommendation

Chuhan Wu, Fangzhao Wu, Tao Qi +1

Diversity is an important factor in providing high-quality personalized news recommendations. However, most existing news recommendation methods only aim to optimize recommendation…