A Comparative Study of Web-pages Classification Methods using Fuzzy Operators Applied to Arabic Web-pages
In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
@article{"International Journal of Information, Control and Computer Sciences:61343", author = "Ahmad T. Al-Taani and Noor Aldeen K. Al-Awad", title = "A Comparative Study of Web-pages Classification Methods using Fuzzy Operators Applied to Arabic Web-pages", abstract = "In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
", keywords = "Text classification, HTML, web pages, machine learning, fuzzy logic, Arabic web pages.", volume = "1", number = "7", pages = "2174-3", }