29 citations · 97 across the 19 of their papers we have counts for
15 papers · 1 filter
On the Sweet Spot of Contrastive Views for Knowledge-enhanced Recommendation
Haibo Ye, Xinjie Li, Yuan Yao +1
In recommender systems, knowledge graph (KG) can offer critical information that is lacking in the original user-item interaction graph (IG). Recent process has explored this direc…
Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-link Diagrams
Qing Chen, Nan Chen, Wei Shuai +4
Graph or network data are widely studied in both data mining and visualization communities to review the relationship among different entities and groups. The data facts derived fr…
Ensuring User-side Fairness in Dynamic Recommender Systems
Hyunsik Yoo, Zhichen Zeng, Jian Kang +7
User-side group fairness is crucial for modern recommender systems, aiming to alleviate performance disparities among user groups defined by sensitive attributes like gender, race,…
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu, Ruizhong Qiu, Zhichen Zeng +7
Class imbalance is prevalent in real-world node classification tasks and poses great challenges for graph learning models. Most existing studies are rooted in a class-rebalancing (…
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
Dongqi Fu, Wenxuan Bao, Ross Maciejewski +2
In graph machine learning, data collection, sharing, and analysis often involve multiple parties, each of which may require varying levels of data security and privacy. To this end…
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders
Dingsu Wang, Yuchen Yan, Ruizhong Qiu +4
Multivariate time series (MTS) imputation is a widely studied problem in recent years. Existing methods can be divided into two main groups, including (1) deep recurrent or generat…