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cs.IR2024
Dynamic User Interest Augmentation via Stream Clustering and Memory Networks in Large-Scale Recommender Systems
Peng Liu, Nian Wang, Cong Xu +3
Recommender System (RS) provides personalized recommendation service based on user interest. However, lots of users' interests are sparse due to lacking consumption behaviors, maki…
cs.IR2022★ 54 cited
Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder
Xu Zhao, Yi Ren, Ying Du +2
Embedding & MLP has become a paradigm for modern large-scale recommendation system. However, this paradigm suffers from the cold-start problem which will seriously compromise the e…