Dhiya: A stemmer for morphological level analysis of Gujarati language

Abstract

To understand a language, analysis has to be done at word level, sentence level, context level and discourse level. Morphological analysis comes at the base of all, as it is the first step to understand a given sentence. One of the tasks that can be done at morphological level is stemming. To identify the stem term of a given word is stemming. Stemming is one of the important activities which is not just related to Natural Language Processing domain, but is equally important in Information Retrieval domain. In this paper, authors suggest DHIYA a stemmer for Gujarati language. This stemmer is based on the morphology of Gujarati language. To develop the stemmer, inflections which appeared most in Gujarati text were identified. Based on it, the rule set was created. For training and evaluation of the stemmer's performance the EMILLE corpus is used. The accuracy of the stemmer is 92.41%.