Esra'a Alshdaifat

Orcid: 0000-0002-0551-0849

According to our database1, Esra'a Alshdaifat authored at least 13 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
An Improved Fusion-Based Semantic Similarity Measure for Effective Collaborative Filtering Recommendations.
Int. J. Comput. Intell. Syst., December, 2024

2023
Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks.
J. Ambient Intell. Humaniz. Comput., 2023

2022
A Novel Scheme for Malicious Nodes Detection in Cloud Markets Based on Fuzzy Logic Technique.
Int. J. Interact. Mob. Technol., February, 2022

Predicting student performance: a classification model using machine learning algorithms.
Int. J. Bus. Inf. Syst., 2022

Advances in Contextual Action Recognition: Automatic Cheating Detection Using Machine Learning Techniques.
Data, 2022

2021
Effective heterogeneous ensemble classification: An alternative approach for selecting base classifiers.
ICT Express, 2021

The Effect of Preprocessing Techniques, Applied to Numeric Features, on Classification Algorithms' Performance.
Data, 2021

2017
A Directed Acyclic Graph (DAG) Ensemble Classification Model: An Alternative Architecture for Hierarchical Classification.
Int. J. Data Warehous. Min., 2017

2015
Hierarchical ensemble classification : towards the classification of data collections that feature large numbers of class labels.
PhD thesis, 2015

A Directed Acyclic Graph Based Approach to Multi-Class Ensemble Classification.
Proceedings of the Research and Development in Intelligent Systems XXXII, 2015

2014
A Multi-path Strategy for Hierarchical Ensemble Classification.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2014

2013
Hierarchical Single Label Classification: An Alternative Approach.
Proceedings of the Research and Development in Intelligent Systems XXX, 2013

Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification.
Proceedings of the Advanced Data Mining and Applications, 9th International Conference, 2013


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