Paper Info
Title
Parallel hardware for faster morphological analysis
Abstract
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.
Year
DOI
Venue
2019
10.1016/j.jksuci.2017.07.003
Journal of King Saud University - Computer and Information Sciences
Keywords
DocType
Volume
Morphological analysis,NLP,Performance,Hardware design,FPGAs
Journal
30
Issue
ISSN
Citations 
4
1319-1578
0
PageRank 
References 
Authors
0.34
17
3
Name
Order
Citations
PageRank
Issam W. Damaj1289.84
Mahmoud Imdoukh200.34
Rached Zantout3187.67