Deceptive reviewer group detection using self-adversarial variational autoencoder: a heterogeneous graph-based approach

With the rapid growth of online review platforms and e-commerce websites, user-posted reviews have become an essential factor influencing consumers' purchasing decisions. The growing presence of review spammers who post misleading or biased reviews has raised concerns about the credibility of o...

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Veröffentlicht in:	Knowledge and information systems Jg. 67; H. 11; S. 10581 - 10610
Hauptverfasser:	Maurya, Sushil Kumar, Singh, Dinesh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.11.2025 Springer Nature B.V
Schlagworte:	Behavior Clustering Computer Science Data Mining and Knowledge Discovery Database Management Datasets Deep learning Graphs Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) IT in Business Machine learning Nodes Product reviews Propagation Random walk Spamming Variational autoencoder Self-adversarial Heterogeneous graph Spammer group Clustering Meta-walk
ISSN:	0219-1377, 0219-3116
Online-Zugang:	Volltext
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