27 citations · 33 across the 5 of their papers we have counts for
Showing cs.IRShow all
3 papers · 1 filter
cs.IR2023★ 1 cited
Our Model Achieves Excellent Performance on MovieLens: What Does it Mean?
Yu-chen Fan, Yitong Ji, Jie Zhang +1
A typical benchmark dataset for recommender system (RecSys) evaluation consists of user-item interactions generated on a platform within a time period. The interaction generation m…
cs.IR2023★ 1 cited
Retraining A Graph-based Recommender with Interests Disentanglement
Yitong Ji, Aixin Sun, Jie Zhang
In a practical recommender system, new interactions are continuously observed. Some interactions are expected, because they largely follow users' long-term preferences. Some other…
cs.IR2021★ 27 cited
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems
Danni Peng, Sinno Jialin Pan, Jie Zhang +1
Recommender Systems (RSs) in real-world applications often deal with billions of user interactions daily. To capture the most recent trends effectively, it is common to update the…