DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks

DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks

A significant aspect of today’s digital information is attributed networks, which combine multiple node attributes with the basic network topology to extract knowledge. Anomaly Detection on attributed networks has recently drawn significant attention from researchers and is widely used in...

Full description

Saved in:
Bibliographic Details
Main Authors: Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Anomaly detection
attributed networks
deep learning
dual variational autoencoder
Gaussian mixture model
graph convolution network
Online Access:https://ieeexplore.ieee.org/document/9866699/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/9866699/

Similar Items