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Discovering suffixes: A Case Study for Marathi Language
| Citations: | 3 - 0 self |
BibTeX
@MISC{Majgaonker_discoveringsuffixes:,
author = {Mudassar M. Majgaonker},
title = {Discovering suffixes: A Case Study for Marathi Language},
year = {}
}
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Abstract
Abstract — Suffix stripping is a pre-processing step required in a number of natural language processing applications. Stemmer is a tool used to perform this step. This paper presents and evaluates a rule-based and an unsupervised Marathi stemmer. The rule-based stemmer uses a set of manually extracted suffix stripping rules whereas the unsupervised approach learns suffixes automatically from a set of words extracted from raw Marathi text. The performance of both the stemmers has been compared on a test dataset consisting of 1500 manually stemmed word. Keywords-component; Marathi morphology, Marathi stemmer, Unsupervised stemmer, Rule-based stemmer, Natural language processing
Keyphrases
marathi language case study rule-based stemmer natural language processing application raw marathi text unsupervised approach abstract suffix stripping unsupervised marathi stemmer suffix stripping rule natural language processing marathi stemmer marathi morphology test dataset consisting pre-processing step
