Discovering suffixes: A Case Study for Marathi Language
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 8
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 temmed word.
Authors and Affiliations
Mudassar M. Majgaonker , Tanveer J Siddiqui
Keywords
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