1 citations · 1 across the 7 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024
Labor Migration Modeling through Large-scale Job Query Data
Zhuoning Guo, Le Zhang, Hengshu Zhu +3
Accurate and timely modeling of labor migration is crucial for various urban governance and commercial tasks, such as local policy-making and business site selection. However, exis…
cs.LG2024★ 1 cited
Convergence-aware Clustered Federated Graph Learning Framework for Collaborative Inter-company Labor Market Forecasting
Zhuoning Guo, Hao Liu, Le Zhang +3
Labor market forecasting on talent demand and supply is essential for business management and economic development. With accurate and timely forecasts, employers can adapt their re…
cs.IR2024
DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
Leilei Ding, Dazhong Shen, Chao Wang +3
Graph Convolutional Networks (GCNs) have become pivotal in recommendation systems for learning user and item embeddings by leveraging the user-item interaction graph's node informa…