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A Review for Arabic Sentiment Analysis Using Deep Learning
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     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include pre-processing, feature extraction and classification, as well as the datasets used. In the end, all the research works are compared in terms of their methodology and results. The findings demonstrated that the majority of deep learning models, including CNN and LSTM, outperformed many of the machine learning models analyzed, and that the size of the training datasets had a direct correlation with the model's performance. Where larger datasets resulted in more successful model training.

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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
A new smart approach of an efficient energy consumption management by using a machine-learning technique
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Comparing the Random Forest vs. Extreme Gradient Boosting using Cuckoo Search Optimizer for Detecting Arabic Cyberbullying
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   Cyberbullying is one of the major electronic problems, and it is not a new phenomenon. It was present in the traditional form before the emergence of social networks, and cyberbullying has many consequences, including emotional and physiological states such as depression and anxiety. Given the prevalence of this phenomenon and the importance of the topic in society and its negative impact on all age groups, especially adolescents, this work aims to build a model that detects cyberbullying in the comments on social media (Twitter) written in the Arabic language using Extreme Gradient Boosting (XGBoost) and Random Forest methods in building the models. After a series of pre-processing, we found that the accuracy of classification of t

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Treatment of Nasopharyngeal Carcinoma by Using Deep X-Ray Therapy
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Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin

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Publication Date
Mon May 01 2023
Journal Name
Complementary Therapies In Medicine
Effects of almond intake on oxidative stress parameters: A systematic review and meta-analysis of clinical trials
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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
Differences of Style between English and Arabic Political Discourse: A Contrastive Study
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Traditionally, style is defined as the expressive, emotive or aesthetic emphasis added linguistically to the discourse with its meaning is the same. In the current study, however, style is defined as the linguistic choice that the language users can make for specific purposes.

    This study, thus, aims at analyzing political Arabic and English speeches to find out whether there are differences of style between English and Arabic and whether the choices the language users make  can show any traits of their psychological status.

    To fulfill the above aims, the study hypothesizes that English and Arabic  speeches can be analyzed stylistically and that there are stylistic difference

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for New COVID-19 Cases Using Recurrent Neural Networks and Long-Short Term Memory
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     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470

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Publication Date
Sun Mar 03 2024
Journal Name
The Science Teacher
Using Scenarios to Assess Student Learning
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Publication Date
Tue Nov 15 2022
Journal Name
Nasaq Journal
Componential Analysis of Hatred Synonymy in the Lexicons of English and Standard Arabic
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ABSTRACT This paper has a three-pronged objective: offering a unitary set of semantic distinctive features to the analysis of nominal “hatred synonyms” in the lexicon of both English and Standard Arabic (SA), applying it procedurally to test its scope of functionality crosslinguistically, and singling out the closest noun synonymous equivalents among the membership of the two sets in this particular lexical semantic field in both languages. The componential analysis and the matching procedures carried have been functional in identifying ten totally matching equivalents (i.e. at 55.6%), and eight partially matching ones (i.e. at %44.4%). This result shows that while total matching equivalences do exist in the translation of certain Eng

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