Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2005
Title: Effectiveness of rule-based classifiers in Sinhala text categorization
Authors: Haddela, P. S
Lakmali, K. B. N
Keywords: Effectiveness
rule-based classifiers
Sinhala text
categorization
Issue Date: 14-Sep-2017
Publisher: IEEE
Citation: K. B. N. Lakmali and P. S. Haddela, "Effectiveness of rule-based classifiers in Sinhala text categorization," 2017 National Information Technology Conference (NITC), 2017, pp. 153-158, doi: 10.1109/NITC.2017.8285655.
Series/Report no.: 2017 National Information Technology Conference (NITC);Pages 153-158
Abstract: In the recent past, the growth of Sinhala text usage on the web has been increasing rapidly due to the advancement in the field of information and communication technologies in Sri Lanka. With this change in society, automatic text categorization becomes important for many operations in computing. Therefore, the aim of this research is to assess commonly used rule based text classification algorithms against the Sinhala dataset. This study is limited to rule based classifiers as they are humanly interpretable by nature, which gives an added advantage to text classification. This paper presents a. The comparison of experiment results of rule based classifiers b. SinNG5 corpus and Sinhala stop word list named as SinSWL. The corpus and stop word list are freely available for academic researches.
URI: http://rda.sliit.lk/handle/123456789/2005
ISBN: 978-1-5386-2425-8
Appears in Collections:Department of Information Technology-Scopes
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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