Implemented Stemming Algorithms for Six Ethiopian Languages

Abstract

Text stemming is an exploratory process of removing suffixes, infixes and sometimes prefixes from words
to arrive at the base word. It is one of the pipeline features of most Natural Language Processing
Applications (NLPAs) and commonly used in natural language processing (NLP) and in text mining. The
main problems of developing stemming are to identify and remove any kind of affixes since all the six
languages those I have selected for analysis have different characteristics, sentence structures and
grammatical rules. This paper tries to analysis different approaches that have been implemented by
different researchers or scholars of the selected languages accordingly. I have discussed the type of
stemming approaches, an overview of the available and the most popular used stemmers for selected
languages and brief analysis between discussed stemmers as well as their evaluation results and analysis
of available stemmers on the languages experimentally. Based on the analysis study and experiment, I have
concluded and recommended the final results of the stemmer for the languages