Nazeeh Ghatasheh
Publications
25
h-index
7
Citations
188
Highly Influential Citations
6
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Predicting Customer Churn in Telecom Industry using Multilayer Preceptron Neural Networks : Modeling and Analysis
O. Adwan, Hossam Faris, K. Jaradat, Osama Harfoushi, Nazeeh Ghatasheh, King Abdullah
2014
Churn represents the problem of losing a customer to another business competitor which leads to serious profit loss. Therefore, many companies investigate different techniques that can predict churn… Expand
26 Citations
2
PDF
Data Security Issues and Challenges in Cloud Computing: A Conceptual Analysis and Review
Osama Harfoushi, Bader M. AlFawwaz, Nazeeh Ghatasheh, Ruba Obiedat, M. Abu-Faraj, Hossam Faris
Computer Science
23 January 2014
TLDR
Security is one of the main challenges that hinder the growth of cloud computing and service providers strive to reduce the risks over the clouds and increase their reliability in order to build mutual trust between them and the cloud customers. Expand
27 Citations
2
PDF
Optimizing Software Effort Estimation Models Using Firefly Algorithm
Nazeeh Ghatasheh, Hossam Faris, Ibrahim Aljarah, R. Al-Sayyed
Computer Science, MathematicsArXiv
3 March 2015
TLDR
Experimental results show high accuracy and significant error minimization of Firefly Algorithm over other metaheuristic optimization algorithms including Genetic Algorithms and Particle Swarm Optimization.Expand
37 Citations
1
PDF
Knowledge Level Assessment in e-Learning Systems Using Machine Learning and User Activity Analysis
Nazeeh Ghatasheh
Computer Science
2015
TLDR
A modern design of a dynamic learning environment that goes along the most recent trends in e-Learning is proposed, and an overall performance superiority of a support vector machine model in evaluating the knowledge levels is illustrated. Expand
18 Citations
1
PDF
Business Analytics using Random Forest Trees for Credit Risk Prediction: A Comparison Study
Nazeeh Ghatasheh
Computer Science
30 November 2014
TLDR
This empirical research aims to evaluate the performance of different Machine Learning algorithms for credit risk prediction with more focus on Random Forest Trees, and concludes that the model based on Random forest Trees overperformed most of the other models. Expand
19 Citations
PDF
Initializing Genetic Programming using Fuzzy Clustering and its Application in Churn Prediction in the Telecom Industry
Bashar Al-Shboul, Hossam Faris, Nazeeh Ghatasheh
Computer Science
10 February 2015
TLDR
A churn prediction framework is proposed aiming at enhancing the predictability of churning customers by combining two heuristic approaches; Fast Fuzzy C-Means (FFCM) and Genetic Programming (GP). Expand
4 Citations
PDF
Business Analytics in Telemarketing: Cost-Sensitive Analysis of Bank Campaigns Using Artificial Neural Networks
Nazeeh Ghatasheh, Hossam Faris, I. Al-Taharwa, Yousra Harb, A. Harb
Computer Science
9 April 2020
TLDR
An interesting Meta-Cost method improved the performance of the prediction model without imposing significant processing overhead or altering original data samples, and proposed enhanced Artificial Neural Network models to mitigate the dramatic effects of highly imbalanced data.Expand
4 Citations
PDF
A Genetic Programming Based Framework for Churn Prediction in Telecommunication Industry
Hossam Faris, Bashar Al-Shboul, Nazeeh Ghatasheh
Computer Science
ICCCI

24 September 2014
TLDR
A churn prediction framework is proposed aiming at enhancing the ability to forecast customer churn, which surpasses various state-of-the-art classification methods for this particular dataset. Expand
20 Citations
Multi-Agent Swarm Spreading Approach in Unknown Environments
Shadi Alian, Nazeeh Ghatasheh, M. Abu-Faraj
2014
Swarm spreading has been gaining more focus since the more reliance on artificial intelligence in solving complex problems. Such importance comes from the various possible applications of the swarm… Expand
5 Citations
Robotics Evolution: from Remote Brain to Cloud
A. Sheta, Nazeeh Ghatasheh, Hossam Faris, A. Rodan
Engineering, Computer ScienceArXiv
8 January 2019
TLDR
This research highlights the advancements in robotic systems with focus on cloud robotics as an emerging trend and offers promising insights for future breed of intelligent, flexible, and autonomous robotic systems in the Internet of Things era. Expand
2 Citations
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