3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.IR2024
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
Yue Ding, Yanbiao Ji, Xun Cai +7
In modern recommender systems, especially in e-commerce, predicting multiple targets such as click-through rate (CTR) and post-view conversion rate (CTCVR) is common. Multi-task re…
cs.IR2024★ 3 cited
Pareto-based Multi-Objective Recommender System with Forgetting Curve
Jipeng Jin, Zhaoxiang Zhang, Zhiheng Li +4
Recommender systems with cascading architecture play an increasingly significant role in online recommendation platforms, where the approach to dealing with negative feedback is a…
cs.SI2023
DSCom: A Data-Driven Self-Adaptive Community-Based Framework for Influence Maximization in Social Networks
Yuxin Zuo, Haojia Sun, Yongyi Hu +2
Influence maximization aims to find a subset of seeds that maximize the influence spread under a given budget. In this paper, we mainly address the data-driven version of this prob…