1 citations · 1 across the 4 of their papers we have counts for
Showing cs.IRShow all
3 papers · 1 filter
cs.IR2025
Collaborative Group-Aware Hashing for Fast Recommender Systems
Yan Zhang, Li Deng, Lixin Duan +2
The fast online recommendation is critical for applications with large-scale databases; meanwhile, it is challenging to provide accurate recommendations in sparse scenarios. Hash t…
cs.IR2020
Collaborative Generative Hashing for Marketing and Fast Cold-start Recommendation
Yan Zhang, Ivor W. Tsang, Lixin Duan
Cold-start has being a critical issue in recommender systems with the explosion of data in e-commerce. Most existing studies proposed to alleviate the cold-start problem are also k…
cs.IR2020
Deep Pairwise Hashing for Cold-start Recommendation
Yan Zhang, Ivor W. Tsang, Hongzhi Yin +3
Recommendation efficiency and data sparsity problems have been regarded as two challenges of improving performance for online recommendation. Most of the previous related work focu…