Web Pages Categorization Based on Classification & Outlier Analysis through FSVM

Authors

  • Geeta R.B Department of Information Technology, GMR Institute of Technology, RAJAM, AP, India
  • Shobha R.B Department of Electronics and Communications, Basaweshwar Engineering College, Bagalkot, India
  • Shashikumar G Totad Department of Computer Science, GMR Institute of Technology, RAJAM, AP, India
  • Prasad Reddy PVGD Department of CS & SE, Andhra University, Vizag, AP, India

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.

Keywords:

Support vector machine, Outliers, Categorization, Log file, Kernel parameters, Web page

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Published

2014-03-20

How to Cite

R.B, G. ., R.B, S. ., Totad, S. G., & PVGD, P. R. . (2014). Web Pages Categorization Based on Classification & Outlier Analysis through FSVM. Review of Computer Engineering Research, 1(1), 19–30. Retrieved from https://archive.conscientiabeam.com/index.php/76/article/view/1433

Issue

Vol. 1 No. 1 (2014)

Section

Articles