Assamese Inflectional Rule-Based Stemmer

Mandira Neog; Nomi Baruah

doi:10.17485/IJST/v16iSP2.6447

Article

Assamese Inflectional Rule-Based Stemmer

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16iSP2.6447

Year: 2023, Volume: 16, Issue: Special Issue 2, Pages: 38-43

Original Article

Assamese Inflectional Rule-Based Stemmer

Mandira Neog^1*, Nomi Baruah²

¹Research Scholar, Centre for Computer Science and Application, Dibrugarh University, Assam, India
²Associate Professor, Department of Computer Science & Engineering, DUIET, Dibrugarh University, Assam, India

*Corresponding Author
Email: [email protected]

Received Date:23 March 2023, Accepted Date:26 June 2023, Published Date:02 November 2023

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The research paper presents an Assamese Inflectional Rule-Based Stemmer with supervised rules that tackles the issues brought on by the language’s complex morphology. Objectives: The goal is to create a stemmer that accurately captures a word’s context while taking its inflectional forms into account. Methods: This was accomplished using a rule-based approach that had been improved by the incorporation of Parts-Of-Speech tagged (POS-tagged) data with Assamese WordNet. A corpus of 50,000 words from diverse sources was used, together with POS-tagged data. Assamese WordNet was also added to improve the stemmer’s performance. Findings: An accuracy of 91% achieved utilising the tagged data, surpassing the 86% accuracy attained without the use of tags, the evaluation findings showed a substantial improvement. The suggested stemmer successfully captures word meanings and their inflectional variations by combining POS tagging and utilizing Assamese WordNet. Novelty: Applications like sentiment analysis and information retrieval systems benefit from this research’s advancement of Assamese language processing. The development of accurate stemming methods successfully closes the prevailing gap in elemental processing. This development enables information retrieval systems to operate more quickly and accurately.

Keywords: Stemming, POStag, NLP, Suffix, Prefix

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Copyright

© 2023 Neog & Baruah. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)