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20202023
most citedA Semi-supervised Graph Attentive Network for Financial Fraud Detection

364 citations · 415 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.SI2022

An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022

Qian Zhao, Shuo Yang, Binbin Hu +5

Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area. The WSDM Cup 2022 seeks for solutions that pre…

cs.SI20209 cited

Heterogeneous Graph Neural Network for Recommendation

Jinghan Shi, Houye Ji, Chuan Shi +3

The prosperous development of e-commerce has spawned diverse recommendation systems. As a matter of fact, there exist rich and complex interactions among various types of nodes in…

cs.SI2020

AGL: a Scalable System for Industrial-purpose Graph Machine Learning

Dalong Zhang, Xin Huang, Ziqi Liu +8

Machine learning over graphs have been emerging as powerful learning tools for graph data. However, it is challenging for industrial communities to leverage the techniques, such as…

cs.SI2020

DSSLP: A Distributed Framework for Semi-supervised Link Prediction

Dalong Zhang, Xianzheng Song, Ziqi Liu +4

Link prediction is widely used in a variety of industrial applications, such as merchant recommendation, fraudulent transaction detection, and so on. However, it's a great challeng…

cs.SI2020364 cited

A Semi-supervised Graph Attentive Network for Financial Fraud Detection

Daixin Wang, Jianbin Lin, Peng Cui +7

With the rapid growth of financial services, fraud detection has been a very important problem to guarantee a healthy environment for both users and providers. Conventional solutio…

cs.SI2020

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

Ziqi Liu, Dong Wang, Qianyu Yu +8

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited…