Semantically enhanced machine learning approach to recommend e-learning content

E Learning ◽

Semantically Enhanced

Semantically enhanced machine learning approach to recommend e-learning content

International Journal of Electronic Business ◽

10.1504/ijeb.2020.111095 ◽

2020 ◽

Vol 15 (4) ◽

pp. 389

Author(s):

Hadi Ezaldeen ◽

Rachita Misra ◽

Rawaa Alatrash ◽

Rojalina Priyadarshini

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Learning Content ◽

E Learning ◽

Semantically Enhanced

Rough set and machine learning approach for identifying flow experience in e-learning

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/732/1/012047 ◽

2020 ◽

Vol 732 ◽

pp. 012047

Author(s):

D S S Sahid ◽

R Efendi ◽

E H Putra

Keyword(s):

Machine Learning ◽

Rough Set ◽

Flow Experience ◽

Learning Approach ◽

Towards e-learning security: A machine learning approach

International Conference on Information Society (i-Society 2011) ◽

10.1109/i-society18435.2011.5978544 ◽

2011 ◽

Cited By ~ 4

Author(s):

Taiwo Ayodele ◽

Charles A. Shoniregun ◽

Galyna Akmayeva

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Advances in Intelligent Systems and Computing - Advanced Intelligent Systems for Sustainable Development (AI2SD’2018) ◽

A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

10.1007/978-3-030-11928-7_70 ◽

2019 ◽

pp. 772-786 ◽

Cited By ~ 1

Author(s):

Ouafae El Aissaoui ◽

Yasser El Madani El Alami ◽

Lahcen Oughdir ◽

Youssouf El Allioui

Keyword(s):

Machine Learning ◽

Learning Styles ◽

Learning System ◽

Learning Approach ◽

E Learning ◽

Hybrid Machine

A machine learning approach for student assessment in E-learning using Quinlan's C4.5, Naive Bayes and Random Forest algorithms

2016 19th International Multi-Topic Conference (INMIC) ◽

10.1109/inmic.2016.7840094 ◽

2016 ◽

Cited By ~ 5

Author(s):

Tahira Mahboob ◽

Sadaf Irfan ◽

Aysha Karamat

Keyword(s):

Machine Learning ◽

Random Forest ◽

Naive Bayes ◽

Student Assessment ◽

Naïve Bayes ◽

Learning Approach ◽

Question Classification for e-Learning Using Machine Learning Approach

2019 International Conference on ICT for Smart Society (ICISS) ◽

10.1109/iciss48059.2019.8969811 ◽

2019 ◽

Author(s):

Oktariani Nurul Pratiwi ◽

Yenie Syukriyah

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Question Classification ◽

PREDICTIVE ANALYTICS FOR E-LEARNING SYSTEM USING MACHINE LEARNING APPROACH

JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES ◽

10.26782/jmcms.2020.02.00017 ◽

2020 ◽

Vol 15 (2) ◽

Author(s):

S.V.N Sreenivasu

Keyword(s):

Machine Learning ◽

Predictive Analytics ◽

Learning System ◽

Learning Approach ◽

Constructing and Validating Geographically Refined HAZUS-MH4 Hurricane Wind Risk Models: A Machine Learning Approach

Advances in Hurricane Engineering ◽

10.1061/9780784412626.092 ◽

2012 ◽

Cited By ~ 2

Author(s):

D. Subramanian ◽

J. Salazar ◽

L. Duenas-Osorio ◽

R. Stein

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Risk Models ◽

Hurricane Wind ◽

Machine Learning Approach

The impact of economic plans on the Chinese education system: a machine learning approach

CADMO ◽

10.3280/cad2018-001005 ◽

2018 ◽

pp. 37-49

Author(s):

Wenjun Lin ◽

Xuefu Xu ◽

Francesco Dell’Anna

Keyword(s):

Machine Learning ◽

Education System ◽

Learning Approach ◽

Chinese Education ◽

System A ◽

The Impact

Improving Bandwidth Utilization and Fairness between TCP Flows based on a Machine-learning Approach

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.133.1259 ◽

2013 ◽

Vol 133 (6) ◽

pp. 1259-1268

Author(s):

Akihiro Shiozu ◽

Syunji Yazaki ◽

K^|^ocirc;ki Abe

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Bandwidth Utilization ◽

Machine Learning Approach