Neveen Hijazi

Harris Hawks Feature Selection in Distributed Machine Learning for Secure IoT Environments

arXiv (Cornell University), Feb 20, 2023

A parallel metaheuristic approach for ensemble feature selection based on multi-core architectures

Expert Systems with Applications, 2021

Abstract Ensemble learning have emerged as a useful machine learning technique, which is based on... more Abstract Ensemble learning have emerged as a useful machine learning technique, which is based on the idea that combining the output of multiple models instead of using a single model. This practice, known as “diversity”, and it usually enhances the performance. On other hand, ensemble feature selection method is based on the same idea, where multiple feature subsets are combined to select an optimal subset of features. Learning methods have difficulties with the dimensionality curse that impact the performance and increase the time exponentially. To overcome this issue, we propose a parallel heterogeneous ensemble feature selection based on three well-regarded algorithms: genetic algorithm, particle swarm optimizer, and grey wolf optimizer. The proposed approach is based on four phases; namely, distribution phase, parallel ensemble feature selection phase, combining and aggregation phase, and testing phase. Three implementations of the proposed approach are presented: a sequential approach running on the central processing unit (CPU), a parallel approach running on multi-core CPU, and a parallel approach running on multi-core CPU with graphics processing units (GPU). To assess the performance of the proposed approach twenty-one large datasets were used. The results show that the proposed parallel approach improved the performance in terms of the prediction results and running time.

Improvement on Cluster Based Routing Protocol by Using Vice Cluster Head

2010 Fourth International Conference on Next Generation Mobile Applications Services and Technologies, 2010

The main objective of routing protocol is to transfer data more efficiently from the source to th... more The main objective of routing protocol is to transfer data more efficiently from the source to the destination. All routing protocols have the same in this goal, but the method that adopts to achieve this is different. This paper propose a new modification of CBRP protocol called Vice Cluster Head Cluster Based Routing Protocol (VCH-CBRP) that elect one Vice Cluster

A parallel metaheuristic approach for ensemble feature selection based on multi-core architectures

Expert Syst. Appl., 2021

Ensemble learning have emerged as a useful machine learning technique, which is based on the idea... more Ensemble learning have emerged as a useful machine learning technique, which is based on the idea that combining the output of multiple models instead of using a single model. This practice, known as “diversity”, and it usually enhances the performance. On other hand, ensemble feature selection method is based on the same idea, where multiple feature subsets are combined to select an optimal subset of features. Learning methods have difficulties with the dimensionality curse that impact the performance and increase the time exponentially. To overcome this issue, we propose a parallel heterogeneous ensemble feature selection based on three well-regarded algorithms: genetic algorithm, particle swarm optimizer, and grey wolf optimizer. The proposed approach is based on four phases; namely, distribution phase, parallel ensemble feature selection phase, combining and aggregation phase, and testing phase. Three implementations of the proposed approach are presented: a sequential approach ...

Intelligent detection of hate speech in Arabic social network: A machine learning approach

by Raneem Qaddoura and Neveen Hijazi

Journal of Information Science

Nowadays, cyber hate speech is increasingly growing, which forms a serious problem worldwide by t... more Nowadays, cyber hate speech is increasingly growing, which forms a serious problem worldwide by threatening the cohesion of civil societies. Hate speech relates to using expressions or phrases that are violent, offensive or insulting for a person or a minority of people. In particular, in the Arab region, the number of Arab social media users is growing rapidly, which is accompanied with high increasing rate of cyber hate speech. This drew our attention to aspire healthy online environments that are free of hatred and discrimination. Therefore, this article aims to detect cyber hate speech based on Arabic context over Twitter platform, by applying Natural Language Processing (NLP) techniques, and machine learning methods. The article considers a set of tweets related to racism, journalism, sports orientation, terrorism and Islam. Several types of features and emotions are extracted and arranged in 15 different combinations of data. The processed dataset is experimented using Support...

Intelligent detection of hate speech in Arabic social network: A machine learning approach

Journal of Information Science

Nowadays, cyber hate speech is increasingly growing, which forms a serious problem worldwide by t... more Nowadays, cyber hate speech is increasingly growing, which forms a serious problem worldwide by threatening the cohesion of civil societies. Hate speech relates to using expressions or phrases that are violent, offensive or insulting for a person or a minority of people. In particular, in the Arab region, the number of Arab social media users is growing rapidly, which is accompanied with high increasing rate of cyber hate speech. This drew our attention to aspire healthy online environments that are free of hatred and discrimination. Therefore, this article aims to detect cyber hate speech based on Arabic context over Twitter platform, by applying Natural Language Processing (NLP) techniques, and machine learning methods. The article considers a set of tweets related to racism, journalism, sports orientation, terrorism and Islam. Several types of features and emotions are extracted and arranged in 15 different combinations of data. The processed dataset is experimented using Support...

Software Defect Prediction Using Heterogeneous Ensemble Classification Based on Segmented Patterns

Applied Sciences

Software defect prediction is a promising approach aiming to improve software quality and testing... more Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their limited resources to the modules that are more prone to defects. In this paper, a hybrid heterogeneous ensemble approach is proposed for the purpose of software defect prediction. Heterogeneous ensembles consist of set of classifiers of different learning base methods in which each of them has its own strengths and weaknesses. The main idea of the proposed approach is to develop expert and robust heterogeneous classification models. Two versions of the proposed approach are developed and experimented. The first is based on simple classifiers, and the second is based on ensemble ones. For evaluation, 21 publicly available benchmark datasets are selected to conduct the experiments and benchm...

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Improvement on Cluster Based Routing Protocol by Using Vice Cluster Head

2010 Fourth International Conference on Next Generation Mobile Applications, Services and Technologies, 2010

The main objective of routing protocol is to transfer data more efficiently from the source to th... more The main objective of routing protocol is to transfer data more efficiently from the source to the destination. All routing protocols have the same in this goal, but the method that adopts to achieve this is different. This paper propose a new modification of CBRP protocol called Vice Cluster Head Cluster Based Routing Protocol (VCH-CBRP) that elect one Vice Cluster

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