Machine Learning for Web Page Classification: A Survey

  • safae lassri Ben M'sik Faculty of Science, Hassan II University Casablanca, Morocco
  • EL HABIB BENLAHMAR Ben M'sik Faculty of Science, Hassan II University Casablanca, Morocco
  • Abderrahim TRAGHA Ben M'sik Faculty of Science, Hassan II University Casablanca, Morocco

Abstract

The Internet contains a vast amount of data that is growing exponentially. To exploit this data, a Web information retrieval system and a categorization of internet content based on the classification of web pages are essential. Web page classification has many applications, among them the construction of web directories and the building of focused crawlers. In this paper, we present the characteristics of web page classification, we produce a literature review by summarizing and evaluating all sources related to web page classification crawled automatically from ScienceDirect and Springer websites, we review the different machine learning algorithms used to categorize web pages. Finally, we track the underlying assumptions behind the studied methods.
Published
Sep 14, 2019
How to Cite
LASSRI, safae; BENLAHMAR, EL HABIB; TRAGHA, Abderrahim. Machine Learning for Web Page Classification: A Survey. International Journal of Information Science and Technology, [S.l.], v. 3, n. 5, p. 38 - 50, sep. 2019. ISSN 2550-5114. Available at: <https://innove.org/ijist/index.php/ijist/article/view/137>. Date accessed: 09 aug. 2022.
Section
Special Issue : Machine Learning and Natural Language Processing