51 citations · 95 across the 8 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.IR2023★ 1 cited
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation
Jingtong Gao, Bo Chen, Menghui Zhu +6
Click-Through Rate (CTR) prediction is a fundamental technique in recommendation and advertising systems. Recent studies have shown that implementing multi-scenario recommendations…
cs.IR2023★ 51 cited
HAMUR: Hyper Adapter for Multi-Domain Recommendation
Xiaopeng Li, Fan Yan, Xiangyu Zhao +4
Multi-Domain Recommendation (MDR) has gained significant attention in recent years, which leverages data from multiple domains to enhance their performance concurrently.However, cu…
cs.IR2023★ 8 cited
Multi-Task Deep Recommender Systems: A Survey
Yuhao Wang, Ha Tsz Lam, Yi Wong +8
Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual improvement among tasks considering their shared knowledge. It is an important topic i…