Advancing Author Gender Identification in Modern Standard Arabic with Innovative Deep Learning and Textual Feature Techniques

被引：0

作者：

Himdi, Hanen ^{[1
]}

Shaalan, Khaled ^{[2
]}

机构：

[1] Computer Science and Artificial Intelligence Department, College of Computer Science and Engineering, University of Jeddah, Jeddah,21955, Saudi Arabia

[2] Faculty of Engineering and IT, The British University in Dubai, DIAC Block 11, Dubai P.O. Box 345015, United Arab Emirates

来源：

Information (Switzerland) | / 15卷 / 12期

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D O I：

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学科分类号：

摘要：

Adversarial machine learning - Contrastive Learning - Convolutional neural networks - Deep learning - Distribution transformers - Economic and social effects - Labeled data - Natural language processing systems - Phishing

引用

共 11 条

[1] Semantic textual similarity for modern standard and dialectal Arabic using transfer learning
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PLOS ONE, 2022, 17 (08):
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[5] Gender identification for Egyptian Arabic dialect in twitter using deep learning models
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[8] Comparative analysis of speaker identification performance using deep learning, machine learning, and novel subspace classifiers with multiple feature extraction techniques
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[9] Non-intrusive load monitoring system for similar loads identification using feature mapping and deep learning techniques
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