Comparative Study of Various Persian Stemmers in the Field of Information Retrieval

Fatemeh Momenipour Moghadam and MohammadReza Keyvanpour
Volume: 11, No: 3, Page: 450 ~ 464, Year: 2015
10.3745/JIPS.04.0020
Keywords: Lookup Table Stemmer, Stemmer, Statistical Stemmer, Structural Stemmer
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Abstract
In linguistics, stemming is the operation of reducing words to their more general form, which is called the ‘stem’. Stemming is an important step in information retrieval systems, natural language processing, and text mining. Information retrieval systems are evaluated by metrics like precision and recall and the fundamental superiority of an information retrieval system over another one is measured by them. Stemmers decrease the indexed file, increase the speed of information retrieval systems, and improve the performance of these sys- tems by boosting precision and recall. There are few Persian stemmers and most of them work based on mor- phological rules. In this paper we carefully study Persian stemmers, which are classified into three main clas- ses: structural stemmers, lookup table stemmers, and statistical stemmers. We describe the algorithms of each class carefully and present the weaknesses and strengths of each Persian stemmer. We also propose some metrics to compare and evaluate each stemmer by them.

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Cite this article
IEEE Style
Fatemeh Momenipour Moghadam and MohammadReza Keyvanpour, "Comparative Study of Various Persian Stemmers in the Field of Information Retrieval," Journal of Information Processing Systems, vol. 11, no. 3, pp. 450~464, 2015. DOI: 10.3745/JIPS.04.0020.

ACM Style
Fatemeh Momenipour Moghadam and MohammadReza Keyvanpour, "Comparative Study of Various Persian Stemmers in the Field of Information Retrieval," Journal of Information Processing Systems, 11, 3, (2015), 450~464. DOI: 10.3745/JIPS.04.0020.