Gujarati Text Morphological Analyzer using Rule based Classifier
Published: 2019
Author(s) Name: Neepa Shah, Aneri Boradia |
Author(s) Affiliation: Associate Professor with Department of Computer Science, Gujarat Vidyapith, Ahmedabad, India.
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Abstract
Data and information’s are overloaded on the web and it is a primary problem faced by people and institutions today. Grouping out some useful information from the sentence given in the Gujarati language and remove suffix, prefix and unnecessary characters is the important process of data cleaning and make effective use of our database. These are challenging task for every Indian language due to its rich morphological variance. This paper presents a lightweight Morphological analyzer for Gujarati language using a rule based classifier. Searching a given word in the Gujarati text is called text mining in a Gujarati language but database of the Gujarati stems need to be strengthen so that searching become effective and easy. The source of text mining is the process of stemming. It is normally used in many types of applications such as Natural Language Processing (NLP), Information Retrieval (IR) and Text Mining (TM). In this paper we present a stemming algorithm.
Keywords: Stemmer, Gujarati language, Morphological Analysis, Rule based classifier.
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