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The code link for Cross-Domain Graph Anomaly Detection is wrong. And the author hasn't open the source code.

Hello ,

I hope this message finds you well. I am writing to request the inclusion of our recent paper in your esteemed paper list repository.

Below are the details of the paper:

Title: DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection
Paper: https://ojs.aaai.org/index.php/AAAI/article/view/29067
Code: https://github.com/AtwoodDuan/DGA-GNN
Authors: Mingjiang Duan, Tongya Zheng, Yang Gao, Gang Wang, Zunlei Feng, Xinyu Wang
Published at: AAAI 2024
Key Contributions: Our paper introduces DGA-GNN, a novel approach that leverages dynamic grouping aggregation in Graph Neural Networks for enhanced fraud detection. This methodology not only achieves advanced effectiveness on fraud detection dataset but also addresses a novel scientific challenge related to the non-additivity of features. These contributions underscore the paper's potential impact and relevance to the community.

We believe that our paper aligns well with the themes of your repository and would be a valuable addition, offering unique insights and methodologies that could benefit researchers and practitioners in the field.

Has it been out of maintenance recently?

KDD'21 Workshop: Relational Graph Neural Networks for Fraud Detection in a Super-App environment [link]
SIGIR'20: GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection [code]