A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text حسب M. Ghoniem , Rania

الموضوعات: "…text mining; ontology learning; hybrid models; genetic algorithms; whale optimization algorithm…"
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Bird’s Eye View feature selection for high-dimensional data حسب Samir Brahim Belhaouari (16855434)

"…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …"

A systematic review of text classification research based on deep learning models in Arabic language حسب 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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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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Cyberbullying Detection Model for Arabic Text Using Deep Learning حسب 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 حسب 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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Design of adaptive arrays based on element position perturbations حسب Dawoud, M.M.

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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars حسب Abathar Al-Hamrani (16494884)

"…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V_pred/V_exp) ratio of 0.97 and a coefficient of variation of 17.91%.…"

Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect حسب 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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Auto-indexing Arabic texts based on association rule data mining. (c2015) حسب Rouba G. Nasrallah

"…The model uses the Apriori Algorithm - an association rule algorithm for extracting frequent sets containing related items - to extract relations between words in the texts to be indexed with words from texts that belong to the same category. …"
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Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models حسب 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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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm حسب De Rochechouart, Maxence

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

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

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

On the Optimization of Band Gaps in Periodic Waveguides حسب Jamil Renno (14070771)

"…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …"

Cyberbullying Detection in Arabic Text using Deep Learning حسب 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 حسب 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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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Indexing Arabic texts using association rule data mining حسب Haraty, Ramzi A.

"…Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …"
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Supervised term-category feature weighting for improved text classification حسب 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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