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dc.contributor.authorKirindage, G-
dc.contributor.authorGodewithana, N-
dc.date.accessioned2022-06-02T07:34:53Z-
dc.date.available2022-06-02T07:34:53Z-
dc.date.issued2020-12-18-
dc.identifier.issn978-073810504-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2553-
dc.description.abstractBecause 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.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofseries7th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2020;-
dc.subjectSinhala text classificationen_US
dc.subjecttopic modelingen_US
dc.subjectnatural language processingen_US
dc.subjectmachine learningen_US
dc.titleAutomatic Sinhala News Classification Approach for News Platformsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICETAS51660.2020.9484277en_US
Appears in Collections:Department of Information Technology-Scopes
Research Papers - IEEE
Research Publications -Dept of Information Technology

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