Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2553
Title: Automatic Sinhala News Classification Approach for News Platforms
Authors: Kirindage, G
Godewithana, N
Keywords: Sinhala text classification
topic modeling
natural language processing
machine learning
Issue Date: 18-Dec-2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Series/Report no.: 7th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2020;
Abstract: Because of generating various news articles in large scale, online sources moved into an automatic categorization mechanism. This research has been conducted using LDA topic modeling approach and using other classification algorithms to establish a news categorization solution. Sinhala news websites have only few news categories and do not have any relationships or hierarchies between the categories. Therefore, some users require to search manually and find the necessary articles which are in those categories. Purpose of this study is to build a news categorization model with categorization hierarchies for Sinhala news articles. The goals of the models are to identify the most suitable news category for a related news article and develop hierarchies using generated news categories and assign the news articles according to the hierarchical structure. The final experiments and evaluations show that the solution performs well to solve the automatic categorization problem in Sinhala news platforms.
URI: http://rda.sliit.lk/handle/123456789/2553
ISSN: 978-073810504-8
Appears in Collections:Department of Information Technology-Scopes
Research Papers - IEEE
Research Publications -Dept of Information Technology

Files in This Item:
File Description SizeFormat 
Automatic_Sinhala_News_Classification_Approach_for_News_Platforms.pdf
  Until 2050-12-31
2.66 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.