Anomalous Subgraph Detection in Given Expected Degree Networks With Deep Learning

Anomalous subgraph detection within networks is an important issue in many emerging applications. Existing algorithms, such as graph structure methods and spectral feature methods, usually focus on the special stochastic model (such as the Erdős-Rényi random graph) or may not efficient...

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Podrobná bibliografie

Hlavní autoři:	Mingan Luan, Bo Wang, Yanping Zhao, Fengye Hu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2021-01-01
Edice:	IEEE Access
Témata:	Anomalous subgraph detection given expected degree models deep learning convolutional neural network
On-line přístup:	https://ieeexplore.ieee.org/document/9406022/
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