TY  - JOUR
T1  - A New CMAC Neural Network Model for Content-based Web Page Classification
AU - , Somaiyeh Dehghan AU - , Amir Masoud Rahmani 
JO  - International Journal of Soft Computing
VL  - 4
IS  - 1
SP  - 10
EP  - 15
PY  - 2009
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2009.10.15
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2009.10.15
KW  - Web mining
KW  -Web Content Mining (WCM)
KW  -web page classification
KW  -Cerebellar Model Arithmetic Computer (CMAC) neural network
KW  -feature selection
KW  -web document representation
AB  - 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.
ER  -