Web Page Categorization through Data Mining Classification Techniques on URL Information

Authors

  • R. GeethaRamani  Department of Information Science and Technology, College of Engineering, Anna University, Chennai, India
  • P. Revathy  Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India

Keywords:

Web Page Categorization, Web Usage Mining, C4.5, NASA Dataset, URL Information

Abstract

The usage of web is increasing exponentially every day. The huge deluge of information owing to the web access can be mined to reveal interesting patterns. Web mining is gaining popularity in the recent times. In this paper web page categorization is attempted. Classification of web pages can provide useful information with regard to advertising and recommendations. Earlier techniques have utilised context, source and URL based information for classification of web pages. In this work, web page classification is performed through URL information. The proposed methodology involves data pre-processing, feature vector formulation, C4.5 classification, performance evaluation and prediction of class of web page. The experimentation has been carried out with NASA log dataset. Various classifiers have been utilised and C4.5 proves to yield the best possible results achieving an accuracy of 99.80% using 3 - fold cross validation. The results obtained justify the performance of the proposed methodology.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-12-31

Issue

Volume 3, Issue 8, November-December-2017

Section

Research Articles

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How to Cite

[1]
R. GeethaRamani, P. Revathy, " Web Page Categorization through Data Mining Classification Techniques on URL Information, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.941-946, November-December-2017.