Tashaphyne0.4: a new arabic light stemmer based on rhyzome modeling approach

Abstract

Stemming algorithms are crucial tools for enhancing the information retrieval process in natural language processing. This paper presents a novel Arabic light stemming algorithm called Tashaphyne0.4, the idea behind this algorithm is to extract the most precise ‘roots’, and ‘stems’ from words of an Arabic text. Thus, the proposed algorithm acts as rooter, stemmer, and segmentation tools at the same time. Our approach involves tri-fold phases (i.e., Preparation, Stems-Extractor, and Root-Extractor). Tashaphyne0.4 has shown better results than six other stemmers (i.e., Khoja, ISRI, Motaz/Light10, Tashaphyne0.3, FARASA, and Assem stemmers). The comparison is performed using four different Arabic comprehensive-benchmarks datasets. In conclusion, our proposed stemmer achieved remarkable results and outperformed other competitive stemmers in extracting ‘Roots’ and ‘Stems’.