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DOI 10.1371/journal.pone.0198284

Медицинская библиотека · PloS one · 2018

Residual-based approach for authenticating pattern of multi-style diacritical Arabic texts.

Hakak Saqib, Kamsin Amirrudin, Palaiahnakote Shivakumara, Tayan Omar, Idna Idris Mohd Yamani, Abukhir Khir Zuhaili

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Arabic script is highly sensitive to changes in meaning with respect to the accurate arrangement of diacritics and other related symbols. The most sensitive Arabic text available online is the Digital Qur'an, the sacred book of Revelation in Islam that all Muslims including non-Arabs recite as part of their worship. Due to the different characteristics of the Arabic letters like diacritics (punctuation symbols), kashida (extended letters) and other symbols, it is written and available in different styles like Kufi, Naskh, Thuluth, Uthmani, etc. As social media has become part of our daily life, posting downloaded Qur'anic verses from the web is common. This leads to the problem of authenticating the selected Qur'anic passages available in different styles. This paper presents a residual approach for authenticating Uthmani and plain Qur'an verses using one common database. Residual (difference) is obtained by analyzing the differences between Uthmani and plain Quranic styles using XOR operation. Based on predefined data, the proposed approach converts Uthmani text into plain text. Furthermore, we propose to use the Tuned BM algorithm (BMT) exact pattern matching algorithm to verify the substituted Uthmani verse with a given database of plain Qur'anic style. Experimental results show that the proposed approach is useful and effective in authenticating multi-style texts of the Qur'an with 87.1% accuracy.

Для цитирования: Hakak Saqib, Kamsin Amirrudin, Palaiahnakote Shivakumara, Tayan Omar, Idna Idris Mohd Yamani, Abukhir Khir Zuhaili. Residual-based approach for authenticating pattern of multi-style diacritical Arabic texts.. PloS one. 2018. DOI: 10.1371/journal.pone.0198284.

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