Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

“…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text by M. Ghoniem , Rania

Subjects: “…text mining; ontology learning; hybrid models; genetic algorithms; whale optimization algorithm…”
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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…This paper undertakes a systematic review of the latest research in the field of the classification of Arabic texts. Several machine learning techniques can be used for text classification, but we have focused only on the recent trend of neural network algorithms. …”
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Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

“…Purpose The purpose of this paper is to propose a new model to enhance auto-indexing Arabic texts. The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…However, the meta-analysis shows that ML approaches, particularly DL, have not been extensively studied for the Arabic text classification of cyberbullying. Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…However, the meta-analysis shows that ML approaches, particularly DL, have not been extensively studied for the Arabic text classification of cyberbullying. Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…Moreover, the proposed model is applied to the database of the Algerian dialect, which contains long Arabic texts, in order to see the efficiency of the proposed model for short and long texts. …”
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Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models by AL SHAMSI, ARWA AHMED

“…However, to our knowledge, no study involved employing deep learning models to conduct sentiment analysis on the Emirati dialect texts. …”
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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”

Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

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An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. …”

Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…Therefore, this study aims to evaluate several versions of Recurrent Neural Networks (RNNs) and Feedforward Neural Networks (FNNs) for detecting cyberbullying in the Arabic language. Although these algorithms are widely used in text classification and outperform the performance of classical classifiers, many have been extensively investigated in other domains such as sentiment analysis and dialect identification, as well as cyberbullying detection in English text. …”
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Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

“…This made finding certain text classification algorithms that fit a specific language or a set of languages a difficult task for researchers. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Supervised term-category feature weighting for improved text classification by Attieh, Joseph

“…Experimental results on five benchmark datasets show that our lean approaches mostly improve text classification accuracy while requiring significantly less computation time compared with their deep model alternatives.…”
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Using Text Mining and Clustering Techniques on Tweets to Discover Trending Topics in Dubai by Hamadeh, Moutaz Wajih

“…Tweets corpus of Dubai were collected, they were presented through the bag of words model using TF-IDF weighting scheme, after that the output of text transformation was introduced to k-means clustering algorithm with cosine similarity measure. …”
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Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …”
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