Comparative Analysis of Stemming Algorithms for Web Text Mining

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Muhammad Haroonb 1,*

1. Department of Computing & Information Technology University of Gujrat Lahore Sub Campus, Lahore, Pakistan

* Corresponding author.


Received: 18 Jul. 2018 / Revised: 29 Jul. 2018 / Accepted: 7 Aug. 2018 / Published: 8 Sep. 2018

Index Terms

Stemming Algorithms, Stemmers, Information Retrieval, NLP, Morphology, Web Mining


As the massive data is increasing exponentially on web and information retrieval systems and the data retrieval has now become challenging. Stemming is used to produce meaningful terms by stemming characters which finally result in accurate and most relevant results. The core purpose of stemming algorithm is to get useful terms and to reduce grammatical forms in morphological structure of some language. This paper describes the different types of stemming algorithms which work differently in different types of corpus and explains the comparative study of stemming algorithms on the basis of stem production, efficiency and effectiveness in information retrieval systems.

Cite This Paper

Muhammad Haroon, " Comparative Analysis of Stemming Algorithms for Web Text Mining", International Journal of Modern Education and Computer Science(IJMECS), Vol.10, No.9, pp. 20-25, 2018. DOI:10.5815/ijmecs.2018.09.03


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