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Author Singh, Jasmeet ♦ Gupta, Vishal
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Text stemming ♦ Corpus-based stemming ♦ Morphological analysis ♦ Rule-based stemming ♦ Statistical stemming ♦ Stemmers
Abstract 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.
Description Author Affiliation: Panjab University, Chandigarh, India (Singh, Jasmeet; Gupta, Vishal)
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-09-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 49
Issue Number 3
Page Count 46
Starting Page 1
Ending Page 46


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Source: ACM Digital Library