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20182025
most citedEnhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

600 citations · 1.6k across the 17 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.CL2021★ 1 cited

Cross-lingual COVID-19 Fake News Detection

Jiangshu Du, Yingtong Dou, Congying Xia +3

The COVID-19 pandemic poses a great threat to global public health. Meanwhile, there is massive misinformation associated with the pandemic which advocates unfounded or unscientifi…

cs.LG2021

Deep Fraud Detection on Non-attributed Graph

Chen Wang, Yingtong Dou, Min Chen +3

Fraud detection problems are usually formulated as a machine learning problem on a graph. Recently, Graph Neural Networks (GNNs) have shown solid performance on fraud detection. Th…

cs.SI2021★ 153 cited

ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation

Liangwei Yang, Zhiwei Liu, Yingtong Dou +2

Social recommendation aims to fuse social links with user-item interactions to alleviate the cold-start problem for rating prediction. Recent developments of Graph Neural Networks…

cs.SI2021★ 2 cited

User Preference-aware Fake News Detection

Yingtong Dou, Kai Shu, Congying Xia +2

Disinformation and fake news have posed detrimental effects on individuals and society in recent years, attracting broad attention to fake news detection. The majority of existing…

cs.LG2021★ 16 cited

Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks

Jianxin Li, Hao Peng, Yuwei Cao +4

Graph neural networks (GNNs) have been widely used in deep learning on graphs. They can learn effective node representations that achieve superior performances in graph analysis ta…

cs.LG2021★ 20 cited

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Hao Peng, Ruitong Zhang, Yingtong Dou +3

Graph Neural Networks (GNNs) have been widely used for the representation learning of various structured graph data. While promising, most existing GNNs oversimplified the complexi…

cs.LG2021★ 98 cited

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs

Yuwei Cao, Hao Peng, Jia Wu +3

Social events provide valuable insights into group social behaviors and public concerns and therefore have many applications in fields such as product recommendation and crisis man…