Skip to content
Descubridor Institucional UMAR
Inicio
Búsqueda avanzada
Explorar
Inicio
Búsqueda avanzada
Explorar
Login
Language
English
Deutsch
Español
Français
Italiano
All Fields
Title
Author
Subject
Call Number
ISBN/ISSN
Tag
Find
Advanced
Comparing Clustering Algorithms for Collusion Detection Using Mixed‐Type Data
Comparing Clustering Algorithms for Collusion Detection Using Mixed‐Type Data
Fuente:
Wiley Open Access
Saved in:
Bibliographic Details
Main Authors:
Soo Jeong Ingrisone
,
James Ingrisone
Format:
Artículo Open Access
Published:
Wiley
2026
Subjects:
Educational Measurement: Issues and Practice
Online Access:
Acceder al recurso
Tags:
Add Tag
No Tags, Be the first to tag this record!
Cite this
Text this
Email this
Print
Export Record
Export to RefWorks
Export to EndNoteWeb
Export to EndNote
Save to List
Permanent link
Holdings
Description
Comments
Similar Items
Staff View
Internet
https://onlinelibrary.wiley.com/doi/10.1111/emip.70034
Similar Items
On the Cover: Illustrating Collusion Networks with Graph Theory
by: Yuan‐Ling Liaw
Published: (2025)
Detecting Aberrant Test‐Taking Behaviors in Computer‐Based Testing Using One‐Dimensional Convolutional Neural Networks
by: Chunyu Piao, et al.
Published: (2025)
Examining the Psychometric Impact of Targeted and Random Double‐Scoring in Mixed‐Format Assessments
by: Yangmeng Xu, et al.
Published: (2024)
2023 NCME Presidential Address: Some Musings on Comparable Scores
by: Deborah J. Harris
Published: (2024)
Comparative Analysis of Psychometric Frameworks and Properties of Scores from Autogenerated Test Forms
by: Won‐Chan Lee, et al.
Published: (2024)