@Article{pakinsight,
AUTHOR = {},
TITLE = {Web Pages Categorization Based on Classification & Outlier Analysis through FSVM},
JOURNAL = {Review of Computer Engineering Research},
VOLUME = {1},
YEAR = {2014},
NUMBER = {1},
PAGES = {19-30},
URL = {http://www.pakinsight.com/archive/76/03-2014/1},
ISSN = {2410-9142},
ABSTRACT = {The performance of Support Vector Machine is higher than traditional algorithms. The training process of SVM is sensitive to the outliers in the training set. Here in this Paper, a new approach called, Web Pages Categorization based on Classification and Outlier Analysis (WPC-COA), is proposed that uses a polynomial Kernel function to map web page tuples to high dimensional feature space. },
DOI = {}
}