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| 81 |
Comparison of Machine Learning and Sentiment Analysis in Detection of Suspicious Online Reviewers on Different Type of Data
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In: Sensors; Volume 22; Issue 1; Pages: 155 (2021)
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| 82 |
Übersetzungsrelevante Textanalyse. Anhang zum Dossier. Textgrammatik Deutsch
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| 83 |
Comparative Analysis of Reasoning in Russian Classic Poetry
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In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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| 84 |
Weibo Text Sentiment Analysis Based on BERT and Deep Learning
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In: Applied Sciences ; Volume 11 ; Issue 22 (2021)
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| 85 |
Tipps für Deutsch als Fremdsprache Online. Deutsch als 1. und 2 Fremdsprache. Deutsch B, Deutsch C Onlinematerial für den Unterricht
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| 86 |
Tipps für Deutsch als Fremdsprache Online. Deutsch als 1. und 2 Fremdsprache. Deutsch B, Deutsch C Onlinematerial für den Unterricht
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| 87 |
Tipps für Deutsch als Fremdsprache Online. Deutsch als 1. und 2 Fremdsprache. Deutsch B, Deutsch C Onlinematerial für den Unterricht
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| 88 |
Tipps für Deutsch als Fremdsprache Online. Deutsch als 1. und 2 Fremdsprache. Deutsch B, Deutsch C Onlinematerial für den Unterricht
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| 89 |
A Corpus-Based Study of Linguistic Deception in Spanish
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In: Applied Sciences ; Volume 11 ; Issue 19 (2021)
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| 90 |
A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media
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In: Information ; Volume 12 ; Issue 8 (2021)
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| 91 |
Why Do Users of Online Mental Health Communities Get Likes and Reposts: A Combination of Text Mining and Empirical Analysis
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In: Healthcare ; Volume 9 ; Issue 9 (2021)
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| 92 |
Robust Complaint Processing in Portuguese
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In: Information; Volume 12; Issue 12; Pages: 525 (2021)
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| 93 |
Textgrammatik Deutsch. Textwissen Mittel- und Oberstufe DaF für Übersetzer und Dolmetscher. Unterrichtsmaterial Deutsch B, Teil 1
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| 94 |
Textgrammatik Deutsch. Textwissen Mittel- und Oberstufe DaF für Übersetzer und Dolmetscher. Unterrichtsmaterial Deutsch B, Teil 1
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| 95 |
Textgrammatik Deutsch. Textwissen Mittel- und Oberstufe DaF für Übersetzer und Dolmetscher. Unterrichtsmaterial Deutsch B, Teil 1
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| 96 |
Textgrammatik Deutsch. Textwissen Mittel- und Oberstufe DaF für Übersetzer und Dolmetscher. Unterrichtsmaterial Deutsch B, Teil 1
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| 97 |
A Method of Image Quality Assessment for Text Recognition on Camera-Captured and Projectively Distorted Documents
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In: Mathematics ; Volume 9 ; Issue 17 (2021)
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| 98 |
DASentimental: Detecting Depression, Anxiety, and Stress in Texts via Emotional Recall, Cognitive Networks, and Machine Learning
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In: Big Data and Cognitive Computing; Volume 5; Issue 4; Pages: 77 (2021)
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| 99 |
A Novel Deep Learning ArCAR System for Arabic Text Recognition with Character-Level Representation
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In: Computer Sciences & Mathematics Forum; Volume 2; Issue 1; Pages: 14 (2021)
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Abstract:
AI-based text classification is a process to classify Arabic contents into their categories. With the increasing number of Arabic texts in our social life, traditional machine learning approaches are facing different challenges due to the complexity of the morphology and the delicate variation of the Arabic language. This work proposes a model to represent and recognize Arabic text at the character level based on the capability of a deep convolutional neural network (CNN). This system was validated using five-fold cross-validation tests for Arabic text document classification. We have used our proposed system to evaluate Arabic text. The ArCAR system shows its capability to classify Arabic text in character-level. For document classification, the ArCAR system achieves the best performance using the AlKhaleej-balance dataset in terms of accuracy equal to 97.76%. The proposed ArCAR seems to provide a practical solution for accurate Arabic text representation, both for understanding and as a classifications system.
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Keyword:
Arabic character-level representation; Arabic sentiment analysis; Arabic text document classification; deep learning ArCAR system
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URL: https://doi.org/10.3390/IOCA2021-10903
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| 100 |
Political analytics on election candidates and their parties in context of the US Presidential elections 2020
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