15 citations · 18 across the 4 of their papers we have counts for
4 papers
An empirical study of next-basket recommendations
Zhufeng Shao, Shoujin Wang, Qian Zhang +3
Next Basket Recommender Systems (NBRs) function to recommend the subsequent shopping baskets for users through the modeling of their preferences derived from purchase history, typi…
Medical Question Summarization with Entity-driven Contrastive Learning
Wenpeng Lu, Sibo Wei, Xueping Peng +3
By summarizing longer consumer health questions into shorter and essential ones, medical question-answering systems can more accurately understand consumer intentions and retrieve…
A Systematical Evaluation for Next-Basket Recommendation Algorithms
Zhufeng Shao, Shoujin Wang, Qian Zhang +3
Next basket recommender systems (NBRs) aim to recommend a user's next (shopping) basket of items via modeling the user's preferences towards items based on the user's purchase hist…
Aspect-driven User Preference and News Representation Learning for News Recommendation
Rongyao Wang, Wenpeng Lu, Shoujin Wang +3
News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news. Most of existing news recommend…