Comparative analysis of stemming algorithms for web text mining

Автор: Muhammad Haroon

Журнал: International Journal of Modern Education and Computer Science @ijmecs

Статья в выпуске: 9 vol.10, 2018 года.

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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.

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

Короткий адрес: https://sciup.org/15016793

IDR: 15016793   |   DOI: 10.5815/ijmecs.2018.09.03

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