Cargando…

Educational Anomaly Analytics: Features, Methods, and Challenges

Anomalies in education affect the personal careers of students and universities' retention rates. Understanding the laws behind educational anomalies promotes the development of individual students and improves the overall quality of education. However, the inaccessibility of educational data h...

Descripción completa

Detalles Bibliográficos
Autores principales:	Guo, Teng, Bai, Xiaomei, Tian, Xue, Firmin, Selena, Xia, Feng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Big Data
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8795666/ https://www.ncbi.nlm.nih.gov/pubmed/35098114 http://dx.doi.org/10.3389/fdata.2021.811840

Ejemplares similares

Big data analytics and smart cities: applications, challenges, and opportunities
por: Cesario, Eugenio
Publicado: (2023)

Autotuning of Exascale Applications With Anomalies Detection
por: Kimovski, Dragi, et al.
Publicado: (2021)

Anomaly Detection for the Centralised Elasticsearch Service at CERN
por: Andersson, Jennifer R., et al.
Publicado: (2021)

Detecting Group Anomalies in Tera-Scale Multi-Aspect Data via Dense-Subtensor Mining
por: Shin, Kijung, et al.
Publicado: (2021)

Discovering anomalies in big data: a review focused on the application of metaheuristics and machine learning techniques
por: Cavallaro, Claudia, et al.
Publicado: (2023)

Editorial: Big Data Analytics for Precision Health and Prevention
por: Capobianco, Enrico, et al.
Publicado: (2022)

The digitized chronic disease management model: scalable strategies for implementing standardized healthcare and big data analytics in Shanghai
por: Sui, Mengyun, et al.
Publicado: (2023)

Healthcare analytics—A literature review and proposed research agenda
por: Elragal, Rawan, et al.
Publicado: (2023)

Network Models and Simulation Analytics for Multi-scale Dynamics of Biological Invasions
por: Adiga, Abhijin, et al.
Publicado: (2022)

Data Analytics Applications for Streaming Data From Social Media: What to Predict?
por: Emmert-Streib, Frank, et al.
Publicado: (2018)

Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
por: Pitts, Joshua, et al.
Publicado: (2020)

Examining the relationship between big data analytics capabilities and organizational ambidexterity in the Malaysian banking sector
por: Aziz, Norzalita Abd, et al.
Publicado: (2023)

Leveraging extreme scale analytics, AI and digital twins for maritime digitalization: the VesselAI architecture
por: Ilias, Loukas, et al.
Publicado: (2023)

A Policy and Practice Review of Consumer Protections and Their Application to Hospital-Sourced Data Aggregation and Analytics by Third-Party Companies
por: Rahimzadeh, Vasiliki
Publicado: (2021)

Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities
por: Kusters, Remy, et al.
Publicado: (2020)

Editorial: Smart cities challenges, technologies and trends
por: Gupta, Namita
Publicado: (2023)

Research Challenges at the Intersection of Big Data, Security and Privacy
por: Kantarcioglu, Murat, et al.
Publicado: (2019)

Editorial: Ethical challenges in AI-enhanced military operations
por: Helkala, Kirsi Marjaana, et al.
Publicado: (2023)

Changing features of the Northern Hemisphere 500-hPa circumpolar vortex
por: Bushra, Nazla, et al.
Publicado: (2023)

Challenges and Legal Gaps of Genetic Profiling in the Era of Big Data
por: Sariyar, Murat, et al.
Publicado: (2019)

The Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring
por: Laaksonen, Salla-Maaria, et al.
Publicado: (2020)

Comprehensive review for healthcare data quality challenges in blockchain technology
por: AbuHalimeh, Ahmed, et al.
Publicado: (2023)

Abusive Language Detection in Online Conversations by Combining Content- and Graph-Based Features
por: Cécillon, Noé, et al.
Publicado: (2019)

AI-assisted diplomatic decision-making during crises—Challenges and opportunities
por: Pokhriyal, Neeti, et al.
Publicado: (2023)

Significant EHR Feature-Driven T2D Inference: Predictive Machine Learning and Networks
por: Preo, Nicolo', et al.
Publicado: (2019)

Real-world data mining meets clinical practice: Research challenges and perspective
por: Mandreoli, Federica, et al.
Publicado: (2022)

Management of COVID-19 Pandemic Data in India: Challenges Faced and Lessons Learnt
por: Kaur, Jasmine, et al.
Publicado: (2021)

Effects of Feature-Based Explanation and Its Output Modality on User Satisfaction With Service Recommender Systems
por: Zhang, Zhirun, et al.
Publicado: (2022)

Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing
por: Wang, Dongjie, et al.
Publicado: (2021)

The ethics of AI-assisted warfighter enhancement research and experimentation: Historical perspectives and ethical challenges
por: Moreno, Jonathan, et al.
Publicado: (2022)

Solutions to Big Data Privacy and Security Challenges Associated With COVID-19 Surveillance Systems
por: Bentotahewa, Vibhushinie, et al.
Publicado: (2021)

Natural language processing for humanitarian action: Opportunities, challenges, and the path toward humanitarian NLP
por: Rocca, Roberta, et al.
Publicado: (2023)

A Benchmark for Data Imputation Methods
por: Jäger, Sebastian, et al.
Publicado: (2021)

Too much information is no information: how machine learning and feature selection could help in understanding the motor control of pointing
por: Thomas, Elizabeth, et al.
Publicado: (2023)

Untangling Classification Methods for Melanoma Skin Cancer
por: Kumar, Ayushi, et al.
Publicado: (2022)

The comparative ethics of artificial-intelligence methods for military applications
por: Rowe, Neil C.
Publicado: (2022)

Comparative study of minutiae selection methods for digital fingerprints
por: Vibert, Benoit, et al.
Publicado: (2023)

Air Quality Forecast by Statistical Methods: Application to Portugal and Macao
por: Mendes, Luísa, et al.
Publicado: (2022)

Weighting Methods for Rare Event Identification From Imbalanced Datasets
por: He, Jia, et al.
Publicado: (2021)

A concentric circles view of health data relations facilitates understanding of sociotechnical challenges for learning health systems and the role of federated data networks
por: Milne, Richard, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_1glqdfk9nfm3249uvoa4tcb6q0