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Shadi Banitaan
Título
Citado por
Citado por
Año
Efficient Bug Triaging Using Text Mining.
M Alenezi, K Magel, S Banitaan
J. Softw. 8 (9), 2185-2190, 2013
1032013
Bug reports prioritization: Which features and classifier to use?
M Alenezi, S Banitaan
2013 12th International Conference on Machine Learning and Applications 2 …, 2013
722013
A Comparative Analysis of Soft Computing Techniques for Predicting Software Effort Based Use Case Points
M Azzeh, A Nassif, S Banitaan
IET Software 12 (1), 19-29, 2018
552018
Pareto Efficient Multi Objective Optimization for Local Tuning of Analogy Based Estimation
M Azzeh, AB Nassif, S Banitaan, F Almasalha
NEURAL COMPUTING AND APPLICATIONS, 2015
462015
Tram: An approach for assigning bug reports using their metadata
S Banitaan, M Alenezi
2013 Third International Conference on Communications and Information …, 2013
432013
Using data mining to predict possible future depression cases
K Daimi, S Banitaan
International Journal of Public Health Science (IJPHS) 3 (4), 231-240, 2014
372014
Selecting discriminating terms for bug assignment: a formal analysis
I Aljarah, S Banitaan, S Abufardeh, W Jin, S Salem
Proceedings of the 7th International Conference on Predictive Models in …, 2011
332011
Motivations for using social media: comparative study based on cultural differences between American and Jordanian students
H Al-Quraan, E Abu-Shanab, S Banitaan, H Al-Tarawneh
International Journal of Social Media and Interactive Learning Environments …, 2017
222017
Transformed k-nearest neighborhood output distance minimization for predicting the defect density of software projects
C López-Martín, Y Villuendas-Rey, M Azzeh, AB Nassif, S Banitaan
Journal of Systems and Software 167, 110592, 2020
202020
User movement prediction: The contribution of machine learning techniques
S Banitaan, M Azzeh, AB Nassif
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
192016
Support vector regression for predicting the enhancement duration of software projects
C Lopez-Martin, S Banitaan, A Garcia-Floriano, C Yanez-Marquez
2017 16th IEEE International Conference on Machine Learning and Applications …, 2017
162017
Decoba: Utilizing developers communities in bug assignment
S Banitaan, M Alenezi
2013 12th International Conference on Machine Learning and Applications 2, 66-71, 2013
162013
Upsilon-SVR polynomial kernel for predicting the defect density in new software projects
C López-Martín, M Azzeh, A Bou-Nassif, S Banitaan
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
152018
Using categorical features in mining bug tracking systems to assign bug reports
M Alenezi, S Banitaan, M Zarour
arXiv preprint arXiv:1804.07803, 2018
152018
Guest editorial: special issue on predictive analytics using machine learning
AB Nassif, M Azzeh, S Banitaan, D Neagu
Neural Computing and Applications 27, 2153-2155, 2016
132016
Automatic identification of Chagas disease vectors using data mining and deep learning techniques
Z Parsons, S Banitaan
Ecological Informatics, 2021
122021
A better case adaptation method for case-based effort estimation using multi-objective optimization
M Azzeh, AB Nassif, S Banitaan
2014 13th International Conference on Machine Learning and Applications, 409-414, 2014
122014
A partitioning-based approach for robot path planning problems
CY Wang, S Banitaan, J Lyu
2018 18th International Conference on Control, Automation and Systems (ICCAS …, 2018
102018
Class Decomposition using K-means and Hierarchical Clustering
S Banitaan, AB Nassif, M Azzeh
2015 IEEE 14th International Conference on Machine Learning and Applications, 2015
102015
An Application of Classification and Class Decomposition to Use Case Point Estimation Method
M Azzeh, AB Nassif, S Banitaan
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
102015
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