Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding-Reference-Cited by-同舟云学术

Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding

Published:2024 Issue: Volume:12 Page:65555-65569
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Khan Wasim¹^ORCID,Ishrat Mohammad¹^ORCID,Neyaz Khan Ahmad¹^ORCID,Arif Mohammad²^ORCID,Ahamed Shaikh Anwar¹^ORCID,Khubrani Mousa Mohammed³^ORCID,Alam Shadab³^ORCID,Shuaib Mohammed³^ORCID,John Rajan³^ORCID

Affiliation:

1. >Koneru Lakshmaiah Education Foundation, Mangalagiri, Andhra Pradesh, India

2. Vellore Institute of Technology, Vellore, India

3. Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia

Funder

Deanship of Graduate Studies and Scientific Research, Jazan University, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10522661.pdf?arnumber=10522661

Reference71 articles.

1. Robust graph regularization nonnegative matrix factorization for link prediction in attributed networks

2. Graph Data Management, Modeling, and Mining

3. Integrating Entity Attributes for Error-Aware Knowledge Graph Embedding

4. A Pilot Study and Survey on Methods for Anomaly Detection in Online Social Networks

5. AnomMAN: Detect anomalies on multi-view attributed networks

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