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Stemming is a process in which the variant word forms are mapped to their base form. It is among the basic text pre-processing approaches used in Language Modeling, Natural Language Processing, and Information Retrieval applications. In this article, we present a comprehensive survey of text stemming techniques, evaluation mechanisms, and application domains. The main objective of this survey is to distill the main insights and present a detailed assessment of the current state of the art. The performance of some well-known rule-based and statistical stemming algorithms in different scenarios has been analyzed. In the end, we highlighted some open issues and challenges related to unsupervised statistical text stemming. This research work will help the researchers to select the most suitable text stemming technique in a specific application and will also serve as a guide to identify the areas that need attention from the research community.
Singh et al. (Fri,) studied this question.