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Parallel Hardware For Faster Morphological Analysis

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Damaj, Issam (Author)
مؤلفين آخرين: Imdoukh, Mahmoud (Co-Author) , Zantout, Rached (Co-Author)
المجلد/العدد: مج30, ع4
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2018
الصفحات: 531 - 546
DOI: 10.33948/0584-030-004-009
ISSN: 1319-1578
رقم MD: 974507
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
كلمات المؤلف المفتاحية:
Morphological Analysis | NLP | Performance | Hardware Design | Fpgas
رابط المحتوى:
صورة الغلاف QR قانون
حفظ في:
المستخلص: Morphological analysis of Arabic language is computationally intensive, has numerous forms and rules, and intrinsically parallel. The investigation presented in this paper confirms that the effective development of parallel algorithms and the derivation of corresponding processors in hardware enable implementations with appealing performance characteristics. The presented developments of parallel hardware comprise the application of a variety of algorithm modelling techniques, strategies for concurrent processing, and the creation of pioneering hardware implementations that target modern programmable devices. The investigation includes the creation of a linguistic-based stemmer for Arabic verb root extraction with extended infix processing to attain high-levels of accuracy. The implementations comprise three versions, namely, software, non-pipelined processor, and pipelined processor with high throughput. The targeted systems are high-performance multi-core processors for software implementations and high-end Field Programmable Gate Array systems for hardware implementations. The investigation includes a thorough evaluation of the methodology, and performance and accuracy analyses of the developed software and hardware implementations. The developed processors achieved significant speedups over the software implementation. The developed stemmer for verb root extraction with infix processing attained accuracies of 87% and 90.7% for analyzing the texts of the Holy Quran and its Chapter 29 – Surat Al-Ankabut.

ISSN: 1319-1578

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