Classifying Web Pages by Aimed Nation Using Machine Learning
Classifying web pages is to automatically assign predefined class to them. It is one of the main applications of web mining. The authors' aim is to detect the targeted nation based on the web pages content. It is an original application. In this paper, the authors propose different web mining approaches using machine learning algorithms such as Naïve Bayes and Support Vector Machine in order classify them. They present detailed stages of the procedure. The best experimental result based on an original corpus created by their own means shows a very attention grabbing f-score of 85%.
Year of publication: |
2017
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Authors: | Tarik, Boudheb ; Mahmoud, Djelloul Daouadji ; Zakaria, Elberrichi |
Published in: |
International Journal of Organizational and Collective Intelligence (IJOCI). - IGI Global, ISSN 1947-9352, ZDB-ID 2703592-X. - Vol. 7.2017, 1 (01.01.), p. 20-35
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Publisher: |
IGI Global |
Subject: | Supervised Learning | Support Vector Machine | Text Mining | Web Content Mining | Web Page Classification |
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