Results 211 to 220 of about 5,324 (240)

Subsequence kernels-based Arabic text classification

2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), 2014
Kernel methods have known huge success in machine learning. This success is mainly due to their flexibility to deal with high dimensionality of the feature space of complex data such as graphs, trees or textual data. In the field of text classification (TC) their performances have supplanted traditional algorithms.
Attia Nehar, Abdelkader Benmessaoud, Hadda Cherroun, Djelloul Ziadi   +3 more
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Accuracy evaluation of Arabic text classification

2017 12th International Conference on Computer Engineering and Systems (ICCES), 2017
Categorization of Arabic text is a significant challenge nowadays owing to the richness of text that occurs through various modules. Also, the Arabic language is considered the fifth spoken one. During the last decade, scholars incubated few concerns about this regard comparing with English language.
Mostafa Sayed, Rashed Salem, Ayman E. Khedr   +2 more
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Arabic Text Classification in the Legal Domain

2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS), 2019
The field of law in Morocco is behind on progress to other fields, where the archiving of legal documents is done manually and the access to the information is increasingly complex. In the scope of this work, we investigate the application of text classification methods to support law professionals, by proposing a system able to automatically select ...
AIT YAHIA Ikram, LOQMAN Chakir
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Arabic text classification: New study

2017 International Conference on Engineering & MIS (ICEMIS), 2017
Text classification performance is considerably influenced by a factor selected from the text and presented to the classification algorithm: the feature type. Character N-grams, word roots, word stems, and full words have been altogether used as features for Arabic text classification.
Rabii Ayed, Mohamed Labidi, Mohsen Maraoui   +2 more
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Automatic Arabic Text Classification [PDF]

, 2008
Automated document classification is an important text mining task especially with the rapid growth of the number of online documents present in Arabic language. Text classification aims to automatically assign the text to a predefined category based on linguistic features.
Al-Harbi, S, Almuhareb, A, Al-Thubaity, A, Khorsheed, M. S., Al-Rajeh, A   +4 more
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An efficient stemming for Arabic Text Classification

2012 International Conference on Innovations in Information Technology (IIT), 2012
Using N-gram technique without stemming is not appropriate in the context of Arabic Text Classification. For this, we introduce a new stemming technique, which we call “approximate-stemming”, based on the use of Arabic patterns. These are modeled using transducers and stemming is done without depending on any dictionary.
Attia Nehar, Djelloul Ziadi, Hadda Cherroun, Younes Guellouma   +3 more
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Neural Network for Arabic text classification

2009 Second International Conference on the Applications of Digital Information and Web Technologies, 2009
This paper proposes the application of Artificial Neural Network for the classification of Arabic language documents. The automatic classification of Arabic documents using ANN has not been explored in detail so far. In this paper, an Arabic corpus is used to construct and test the ANN model.
Fouzi Harrag, Eyas El-Qawasmah
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Neuro-classification for handwritten Arabic text

ACS/IEEE International Conference on Computer Systems and Applications, 2003. Book of Abstracts., 2004
Summary form only given. The issue of handwritten character recognition is still a big challenge to the scientific community. Several approaches to address this challenge have been attempted in the last years, mostly focusing on the English preprinted or handwritten characters space.
R.A. Haraty, C. Ghaddar
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SCAT: a system of classification for Arabic texts

International Journal of Internet Technology and Secured Transactions, 2011
The core of this work is to realise a system of classification for Arabic texts (SCAT) based on the inter-textual distance theory for Arabic language. This theory assumes the classification of texts according to criteria of lexical statistics, and it is based on the lexical connection approach.
Rami Ayadi, Mohsen Maraoui, Mounir Zrigui   +2 more
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A Review Study on Arabic Text Classification

2022 International Arab Conference on Information Technology (ACIT), 2022
Musab Mustafa Hijazi, Akram M. Zeki, Amelia Ismail   +2 more
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