Titlebook: Anti-Fraud Engineering for Digital Finance; Behavioral Modeling Cheng Wang Book 2023 Tongji University Press 2023 Learning Automata.Fraud

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Knowledge Oriented Strategies: Dedicated Rule Engine,. To address this issue, we propose a Snorkel-based Semi-Supervised GNN (S3GNN). Under S3GNN, we specially design an upgraded version of the rule engines, called . (GOS), a graph-specific extension of Snorkel, a widely-used weakly supervised learning framework, to design rules by subject matter expe

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Associations Dynamic Evolution: Evolving Graph Transformer,pert knowledge is required), and newer works (such as HGT) abandon meta-path and use meta-relation instead, and set up multiple sets of projections The type of matrix modeling edge. From the perspective of dynamics, the past methods mainly used the sequential combination of GNN+RNN (such as TGCN), b

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ing paradigm across a wide array of applications. It covers the latest theoretical and experimental progress and offers important information that is just as relevant for researchers as for professionals..978-981-99-5259-5978-981-99-5257-1

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Verfahrenstechnik in Einzeldarstellungenlment and cross region, which poses great challenges to traditional anti fraud methods. Therefore, the anti fraud technology should also be constantly innovated. It is not only necessary to accurately combat the existing risks, but also to take the lead to prevent problems before they occur. The beh

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Einführung in die Kostenrechnungs occur. The feasibility of our solution is supported by the cooperation of a characteristic and a finding in online payment fraud scenarios: The well-recognized characteristic is that online payment frauds are mostly caused by account compromise. Our finding is that account theft is indeed predicta

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https://doi.org/10.1007/978-3-322-89750-3. To address this issue, we propose a Snorkel-based Semi-Supervised GNN (S3GNN). Under S3GNN, we specially design an upgraded version of the rule engines, called . (GOS), a graph-specific extension of Snorkel, a widely-used weakly supervised learning framework, to design rules by subject matter expe