In this paper, we present a comprehensive evaluation of four Arabic stemmers, based on metrics for correctness, strength and similarity. Two data sets were used in this study. For correctness evaluation, we used a list of 8697 Arabic words grouped into 1606 conceptual classes. For similarity and strength evaluation, we used a list of 72,000 unique Arabic words. Conclusions about correctness, strength and similarity of the four Arabic stemming algorithms are reported.
Daoud, D., & Boitet, C. (2014). Correctness, Strength and Similarity Evaluation of Stemming Algorithms for Arabic. The Egyptian Journal of Language Engineering, 1(1), 17-23. doi: 10.21608/ejle.2014.59847
MLA
Daoud Daoud; Christian Boitet. "Correctness, Strength and Similarity Evaluation of Stemming Algorithms for Arabic", The Egyptian Journal of Language Engineering, 1, 1, 2014, 17-23. doi: 10.21608/ejle.2014.59847
HARVARD
Daoud, D., Boitet, C. (2014). 'Correctness, Strength and Similarity Evaluation of Stemming Algorithms for Arabic', The Egyptian Journal of Language Engineering, 1(1), pp. 17-23. doi: 10.21608/ejle.2014.59847
VANCOUVER
Daoud, D., Boitet, C. Correctness, Strength and Similarity Evaluation of Stemming Algorithms for Arabic. The Egyptian Journal of Language Engineering, 2014; 1(1): 17-23. doi: 10.21608/ejle.2014.59847
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