JSW 2015 Vol.10(4): 454-464 ISSN: 1796-217X
doi: 10.17706/jsw.10.4.454-464
doi: 10.17706/jsw.10.4.454-464
Recognition of Modern Arabic Poems
Abdulrahman Almuhareb, Waleed A. Almutairi, Haya Altuwaijri, Abdulelah Almubarak, Marwa Khan.
King Abdulaziz City for Science and Technology (KACST), The National Center for Computation Technology and Applied Mathematics (CTAM), Riyadh, Kingdom of Saudia Arabia, Saudi.
Abstract—We propose a machine learning method for recognizing modern Arabic poems based on the common poetic features of modern Arabic poetry. The poetic features include: rhyming, repetition, use of diacritics and punctuations, and text alignment. The method can classify text documents as poem or non-poem documents with a very high accuracy of 99.81%.
Index Terms—Meter, poem, poetry, rhyme, verse.
Abstract—We propose a machine learning method for recognizing modern Arabic poems based on the common poetic features of modern Arabic poetry. The poetic features include: rhyming, repetition, use of diacritics and punctuations, and text alignment. The method can classify text documents as poem or non-poem documents with a very high accuracy of 99.81%.
Index Terms—Meter, poem, poetry, rhyme, verse.
Cite: Abdulrahman Almuhareb, Waleed A. Almutairi, Haya Altuwaijri, Abdulelah Almubarak, Marwa Khan., "Recognition of Modern Arabic Poems," Journal of Software vol. 10, no. 4, pp. 454-464, 2015.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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