Authors : Somaiyeh Dehghan and Amir Masoud Rahmani
Abstract: The rapid growth of World Wide Web in recent years, makes it necessary for search engines to classify this data into categories. The automatic classification of web pages deals with text information, structure information and hyperlink information of web pages, which focus research on automatic classification of web text information, that is classification based on content. A major difficulty of content based web page classification is how to deal with high dimensional feature space. Based on the analysis done, CMAC neural network showed faster learning in high dimensional problems. In the present study, the new CMAC neural network model is proposed for use in content based web page classification. The results show that the proposed model is more useful than any other algorithms.
Somaiyeh Dehghan and Amir Masoud Rahmani , 2009. A New CMAC Neural Network Model for Content-based Web Page Classification. International Journal of Soft Computing, 4: 10-15.