Search Results for author: Wei Min

Found 6 papers, 2 papers with code

Modelling graph dynamics in fraud detection with "Attention"

1 code implementation22 Apr 2022 Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang

At online retail platforms, detecting fraudulent accounts and transactions is crucial to improve customer experience, minimize loss, and avoid unauthorized transactions.

Fraud Detection

Explainable Deep Behavioral Sequence Clustering for Transaction Fraud Detection

no code implementations12 Jan 2021 Wei Min, Weiming Liang, Hang Yin, Zhurong Wang, Mei Li, Alok Lal

To utilize the behavior sequence data, we treat click stream data as event sequence, use time attention based Bi-LSTM to learn the sequence embedding in an unsupervised fashion, and combine them with intuitive features generated by risk experts to form a hybrid feature representation.

Fraud Detection

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

no code implementations20 Dec 2020 Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang

Massive account registration has raised concerns on risk management in e-commerce companies, especially when registration increases rapidly within a short time frame.

Frame

xFraud: Explainable Fraud Transaction Detection

1 code implementation24 Nov 2020 Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang

At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss.

Graph Embedding

DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition

no code implementations10 Oct 2019 Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang

Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.

Sequential Behavioral Data Processing Using Deep Learning and the Markov Transition Field in Online Fraud Detection

no code implementations16 Aug 2018 Ruinan Zhang, Fanglan Zheng, Wei Min

Due to the popularity of the Internet and smart mobile devices, more and more financial transactions and activities have been digitalized.

Dynamic Time Warping Fraud Detection

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