doi: 10.17706/jsw.10.4.454-464
Recognition of Modern Arabic Poems
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)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
INSPEC(IET), ULRICH's Periodicals
Directory, WorldCat, etcE-mail: jsweditorialoffice@gmail.com
-
Oct 22, 2024 News!
Vol 19, No 3 has been published with online version [Click]
-
Jan 04, 2024 News!
JSW will adopt Article-by-Article Work Flow
-
Apr 01, 2024 News!
Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec) [Click]
-
Apr 01, 2024 News!
Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP [Click]
-
Jun 12, 2024 News!
Vol 19, No 2 has been published with online version [Click]