Web Page Classification by using CPBF and Neural Network (Review Completed - Accepted)
Normal
0
false
false
false
EN-US
X-NONE
AR-SA
/* Style Definitions */
table.MsoNormalTable
{mso-style-name:”Table Normal”;
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-priority:99;
mso-style-parent:””;
mso-padding-alt:0in 5.4pt 0in 5.4pt;
mso-para-margin:0in;
mso-para-margin-bottom:.0001pt;
text-align:justify;
mso-pagination:widow-orphan;
font-size:10.0pt;
mso-bidi-font-size:9.0pt;
font-family:”Times New Roman”,”serif”;
mso-bidi-font-family:Mangal;}
With the exclusive growth in the WWW makes the internet growing very fast. Therefore classifiers of the web pages become more challenging. The proposed system is about using Class Profile- Based Features CPBF for features selection. In this research, new web page classification method is proposed, using neural network with inputs obtained by CPBF. The fixed number of regular words from each class will be used as a feature vector, these feature vector are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the method provides high quality classification accuracy with the sports news datasets
Keywords: CPBF, Classification, WWW, Web- Page Classification