Classification of News Articles using Supervised Machine Learning Approach
Today the big challenge for NEWS organization to well organize the news and well categorize the news in automatically no need the data entry people to enter and select the category and then based on the category and its sub-category they will be manually selected and enter the details and then after...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The University of Lahore
2020-12-01
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| Series: | Pakistan Journal of Engineering & Technology |
| Subjects: | |
| Online Access: | https://sites2.uol.edu.pk/journals/index.php/pakjet/article/view/589 |
| _version_ | 1818561608881799168 |
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| author | Muhammad Imran Asad Muhammad Abubakar Siddique Safdar Hussain Hafiz Naveed Hassan Jam Munawwar Gul |
| author_facet | Muhammad Imran Asad Muhammad Abubakar Siddique Safdar Hussain Hafiz Naveed Hassan Jam Munawwar Gul |
| author_sort | Muhammad Imran Asad |
| collection | DOAJ |
| description | Today the big challenge for NEWS organization to well organize the news and well categorize the news in automatically no need the data entry people to enter and select the category and then based on the category and its sub-category they will be manually selected and enter the details and then after this the analysis will later on used for different aspects. The news is almost every second used in different sources of media in soft and hard. We use the both sources of the Pakistan News in dual languages English and Urdu both and process them and prepare them for machine learning and based on the Machine learning trained data we build a very effective and efficient model that can predict the title category of the news and category of description of the news. We use different machine learning algorithms and different features extraction finally we build the model using the machine learning algorithm with 89% accuracy with logistic regression. |
| first_indexed | 2024-12-14T00:53:04Z |
| format | Article |
| id | doaj.art-70a603b7b3e54e78bd4728439c46da8f |
| institution | Directory Open Access Journal |
| issn | 2664-2042 2664-2050 |
| language | English |
| last_indexed | 2024-12-14T00:53:04Z |
| publishDate | 2020-12-01 |
| publisher | The University of Lahore |
| record_format | Article |
| series | Pakistan Journal of Engineering & Technology |
| spelling | doaj.art-70a603b7b3e54e78bd4728439c46da8f2022-12-21T23:23:44ZengThe University of LahorePakistan Journal of Engineering & Technology2664-20422664-20502020-12-01332630Classification of News Articles using Supervised Machine Learning ApproachMuhammad Imran Asad0Muhammad Abubakar Siddique1Safdar Hussain2Hafiz Naveed Hassan3Jam Munawwar Gul4Khwaja Fareed University of Engineering and Information Technology, PakistanKhwaja Fareed University of Engineering and Information Technology, PakistanKhwaja Fareed University of Engineering and Information Technology, PakistanKhwaja Freed University of Engineering and Information Technology Rahim Yar Khan, Pakistan Khwaja Freed University of Engineering and Information Technology Rahim Yar Khan, Pakistan Today the big challenge for NEWS organization to well organize the news and well categorize the news in automatically no need the data entry people to enter and select the category and then based on the category and its sub-category they will be manually selected and enter the details and then after this the analysis will later on used for different aspects. The news is almost every second used in different sources of media in soft and hard. We use the both sources of the Pakistan News in dual languages English and Urdu both and process them and prepare them for machine learning and based on the Machine learning trained data we build a very effective and efficient model that can predict the title category of the news and category of description of the news. We use different machine learning algorithms and different features extraction finally we build the model using the machine learning algorithm with 89% accuracy with logistic regression.https://sites2.uol.edu.pk/journals/index.php/pakjet/article/view/589classificationlogistic regressionmachine learningnewsrandom forest |
| spellingShingle | Muhammad Imran Asad Muhammad Abubakar Siddique Safdar Hussain Hafiz Naveed Hassan Jam Munawwar Gul Classification of News Articles using Supervised Machine Learning Approach Pakistan Journal of Engineering & Technology classification logistic regression machine learning news random forest |
| title | Classification of News Articles using Supervised Machine Learning Approach |
| title_full | Classification of News Articles using Supervised Machine Learning Approach |
| title_fullStr | Classification of News Articles using Supervised Machine Learning Approach |
| title_full_unstemmed | Classification of News Articles using Supervised Machine Learning Approach |
| title_short | Classification of News Articles using Supervised Machine Learning Approach |
| title_sort | classification of news articles using supervised machine learning approach |
| topic | classification logistic regression machine learning news random forest |
| url | https://sites2.uol.edu.pk/journals/index.php/pakjet/article/view/589 |
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