A survey on technique for solving web page classification problem

• Main Authors: Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2020
• Subjects: QA76 Computer software; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/28810/1/A%20survey%20on%20technique%20for%20solving%20web%20page.pdf; http://umpir.ump.edu.my/id/eprint/28810/; https://doi.org/10.1088/1757-899X/769/1/012036

Nowadays, the number of web pages on the World Wide Web has been increasing due to the popularity of the Internet usage. The web page classification is needed in order to organize the increasing number of web pages. There are many web page classification techniques that have been proposed by the other researchers. However, there is no comprehensive survey on the performance of the techniques for the web page classification. In this paper, surveys of the different web page classification techniques with the result of the techniques achieved are presented. The existing works of web page classification are reviewed. Based on the survey, we found that the neural network technique namely Convolutional Neural Network (CNN) produce high F-measure value and meet the real-time requirement for classification compared to the other machine learning technique.