Do Words with Certain Part of Speech Tags Improve the Performance of Arabic Text Classification?-Reference-Cited by-同舟云学术

Do Words with Certain Part of Speech Tags Improve the Performance of Arabic Text Classification?

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International Conference on Information System and Data Mining - ICISDM '18
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Author:

Al-Thubaity Abdulmohsen¹,Alqarni Aali¹,Alnafessah Ahmad²

Affiliation:

1. King Abdulaziz City for Science and Technology, Riyadh, KSA

2. Department of Computing, Imperial College London, London, United Kingdom

Publisher

ACM Press

Reference17 articles.

1. Al-Badarneh, A. et al. 2017. The impact of indexing approaches on Arabic text classification. Journal of Information Science. 43, 2 (2017), 159--173.

2. Al-Thubaity, A. et al. 2015. Using Word N-Grams as Features in Arabic Text Classification. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. R. Lee, ed. Springer International Publishing. 35--43.

3. Al-Thubaity, A. and Al-Subaie, A. 2015. Effect of word segmentation on Arabic text classification. 2015 International Conference on Asian Language Processing (IALP).

4. Chang, C.-C. and Lin, C.-J. 2011. LIBSVM: A Library for Support Vector Machines. ACM Trans. Intell. Syst. Technol. 2, 3 (2011), 27:1--27:27. DOI:https://doi.org/10.1145/1961189.1961199.

5. Duwairi, R. et al. 2009. Feature Reduction Techniques for Arabic Text Categorization. J. Am. Soc. Inf. Sci. Technol. 60, 11 (2009), 2347--2352. DOI:https://doi.org/10.1002/asi.v60:11.

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