CLOct 19, 2012
A Lightweight Stemmer for Gujarati
arXiv:1210.5486v226 citations
Originality Synthesis-oriented
AI Analysis
This addresses the need for basic NLP tools in resource-poor languages like Gujarati, but it is incremental as it applies an existing rule-based method to a new language.
The authors tackled the lack of language processing tools for Gujarati by implementing a rule-based stemmer, evaluating it with human expert verification.
Gujarati is a resource poor language with almost no language processing tools being available. In this paper we have shown an implementation of a rule based stemmer of Gujarati. We have shown the creation of rules for stemming and the richness in morphology that Gujarati possesses. We have also evaluated our results by verifying it with a human expert.