Text summarization for news articles by machine learning techniques
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Institute of Engineering Mathematics, Universiti Malaysia Perlis
2023
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my.unimap-777252023-01-25T04:32:16Z Text summarization for news articles by machine learning techniques Chew, XinYing Hew, Zi Jian Olanrewaju Victor Johnson Khaw, Khai Wah xinying@usm.my School of Computer Sciences, 11800, Universiti Sains Malaysia, Pulau Pinang, Malaysia School of Management, 11800, Universiti Sains Malaysia, Pulau Pinang, Malaysia Classifier CNN/Daily Mail Machine Learning News Article Text Summarization Link to publisher's homepage at https://amci.unimap.edu.my/ Text summarizing is very instrumental in natural language text comprehension systems to constructing a text summary using more abstract, condensed knowledge structures. Extractive text summarization is therefore built on language processing to extract the essence sentences of a long text article to produce a summary. Though the known manual process had recorded achievement over time and recently, several machine learning models for extractive text summarization had also been proposed. However, there is a lack of research that benchmark the comparative performance of these machine learning models. This paper, therefore, helps to identify the champion machine learning model in text summarization for news articles and to identify the best text preprocessing method in the machine learning of text summarization. CNN/Daily Mail database is employed for the comparative study of text summarization using chosen classifiers. Random Forest (RF) classifier provides with a champion performance of Rouge-l score, Rouge-2 score and Rouge-L score as 8.2845, 2.884, and 7.9694 respectively. 2023-01-25T04:32:16Z 2023-01-25T04:32:16Z 2022-12 Article Applied Mathematics and Computational Intelligence (AMCI), vol.11(1), 2022, pages 174-196 2289-1315 (print) 2289-1323 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77725 en Institute of Engineering Mathematics, Universiti Malaysia Perlis |
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Universiti Malaysia Perlis |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Classifier CNN/Daily Mail Machine Learning News Article Text Summarization |
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Classifier CNN/Daily Mail Machine Learning News Article Text Summarization Chew, XinYing Hew, Zi Jian Olanrewaju Victor Johnson Khaw, Khai Wah Text summarization for news articles by machine learning techniques |
| description |
Link to publisher's homepage at https://amci.unimap.edu.my/ |
| author2 |
xinying@usm.my |
| author_facet |
xinying@usm.my Chew, XinYing Hew, Zi Jian Olanrewaju Victor Johnson Khaw, Khai Wah |
| format |
Article |
| author |
Chew, XinYing Hew, Zi Jian Olanrewaju Victor Johnson Khaw, Khai Wah |
| author_sort |
Chew, XinYing |
| title |
Text summarization for news articles by machine learning techniques |
| title_short |
Text summarization for news articles by machine learning techniques |
| title_full |
Text summarization for news articles by machine learning techniques |
| title_fullStr |
Text summarization for news articles by machine learning techniques |
| title_full_unstemmed |
Text summarization for news articles by machine learning techniques |
| title_sort |
text summarization for news articles by machine learning techniques |
| publisher |
Institute of Engineering Mathematics, Universiti Malaysia Perlis |
| publishDate |
2023 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77725 |
| _version_ |
1772813101481066496 |