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Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

In today's environment, people can easily use the internet to find information by visiting web pages. Most people like to visit web pages that offer games and videos to watch online. People who spend a lot of time on web pages like these can become addicted to the internet and it can have a bad...

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Main Authors: Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed
Format: Article
Language:English
Published: University of Bahrain 2024
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/40041/1/Use%20Word%20Cloud%20Image%20Of%20Web%20Page%20Text%20Content%20On%20Convolutional%20Neural%20Network%20%28CNN%29%20For%20Classification%20of%20Web%20Pages.pdf
http://umpir.ump.edu.my/id/eprint/40041/
https://journal.uob.edu.bh/handle/123456789/4946
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spelling my.ump.umpir.400412024-01-16T07:23:33Z http://umpir.ump.edu.my/id/eprint/40041/ Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages Siti Hawa, Apandi Jamaludin, Sallim Rozlina, Mohamed QA75 Electronic computers. Computer science QA76 Computer software In today's environment, people can easily use the internet to find information by visiting web pages. Most people like to visit web pages that offer games and videos to watch online. People who spend a lot of time on web pages like these can become addicted to the internet and it can have a bad effect on them. Access to web pages that offer games and streaming videos needs to be limited to stop people from being addicted to the internet. It needs a tool that can classify web pages category based on its content. Due to lack of matrix representation that unable to handle long web page text content, this study uses a technique which is word cloud image to visualize the words that has been extracted from the text content web page after performing data pre-processing. The most popular words from the text content web page are displayed in big size and appear in center of the word cloud image. The most popular words are the words that frequently appear in the text content web page, and it related to describe what the web page content is about. The Convolutional Neural Network (CNN) identifies the pattern of words displayed in the central areas of the word cloud image to classify the category that the web page belongs to. The proposed model for classifying web pages has an accuracy of 0.86. The proposed model can be used, for example, by the institution to set rules and limit the usage of the internet for the users to surf the web pages that offer games and streaming videos. It will be one of the ways to prevent users from getting internet addiction. University of Bahrain 2024-01 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40041/1/Use%20Word%20Cloud%20Image%20Of%20Web%20Page%20Text%20Content%20On%20Convolutional%20Neural%20Network%20%28CNN%29%20For%20Classification%20of%20Web%20Pages.pdf Siti Hawa, Apandi and Jamaludin, Sallim and Rozlina, Mohamed (2024) Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages. International Journal of Computing and Digital Systems, 15 (1). pp. 1-12. ISSN 2210-142X. (Published) https://journal.uob.edu.bh/handle/123456789/4946
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
QA76 Computer software
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Siti Hawa, Apandi
Jamaludin, Sallim
Rozlina, Mohamed
Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
description In today's environment, people can easily use the internet to find information by visiting web pages. Most people like to visit web pages that offer games and videos to watch online. People who spend a lot of time on web pages like these can become addicted to the internet and it can have a bad effect on them. Access to web pages that offer games and streaming videos needs to be limited to stop people from being addicted to the internet. It needs a tool that can classify web pages category based on its content. Due to lack of matrix representation that unable to handle long web page text content, this study uses a technique which is word cloud image to visualize the words that has been extracted from the text content web page after performing data pre-processing. The most popular words from the text content web page are displayed in big size and appear in center of the word cloud image. The most popular words are the words that frequently appear in the text content web page, and it related to describe what the web page content is about. The Convolutional Neural Network (CNN) identifies the pattern of words displayed in the central areas of the word cloud image to classify the category that the web page belongs to. The proposed model for classifying web pages has an accuracy of 0.86. The proposed model can be used, for example, by the institution to set rules and limit the usage of the internet for the users to surf the web pages that offer games and streaming videos. It will be one of the ways to prevent users from getting internet addiction.
format Article
author Siti Hawa, Apandi
Jamaludin, Sallim
Rozlina, Mohamed
author_facet Siti Hawa, Apandi
Jamaludin, Sallim
Rozlina, Mohamed
author_sort Siti Hawa, Apandi
title Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
title_short Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
title_full Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
title_fullStr Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
title_full_unstemmed Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages
title_sort use word cloud image of web page text content on convolutional neural network (cnn) for classification of web pages
publisher University of Bahrain
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/40041/1/Use%20Word%20Cloud%20Image%20Of%20Web%20Page%20Text%20Content%20On%20Convolutional%20Neural%20Network%20%28CNN%29%20For%20Classification%20of%20Web%20Pages.pdf
http://umpir.ump.edu.my/id/eprint/40041/
https://journal.uob.edu.bh/handle/123456789/4946
_version_ 1822924086116876288
score 13.23243

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