Spotting Suspicious Academic Citations Using Self-Learning Graph Transformers

The study introduces a novel approach to identify potential citation manipulation within academic papers. This method utilizes perturbations of a deep embedding model, integrating Graph-Masked Autoencoders to merge textual information with evidence of graph connectivity. Consequently, it yields a mo...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Mathematics (Basel) Jg. 12; H. 6; S. 814
Hauptverfasser:	Avros, Renata, Haim, Mor Ben, Madar, Almog, Ravve, Elena, Volkovich, Zeev
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.03.2024
Schlagworte:	Analysis Citations Computational linguistics Credibility Design Electric transformers Graph representations Graph theory graph-masked autoencoders Language processing manipulated citations Natural language interfaces network perturbation Perturbation
ISSN:	2227-7390, 2227-7390
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!