An Empirical Analysis of Arabic WebPages Classification using Fuzzy Operators
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:64080", author = "Ahmad T. Al-Taani and Noor Aldeen K. Al-Awad", title = "An Empirical Analysis of Arabic WebPages Classification using Fuzzy Operators", 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 documents, Web pages,
Machine learning, Fuzzy logic, Arabic Web pages.", volume = "3", number = "3", pages = "827-6", }