TITLE:
Improved Term Weighting Technique for Automatic Web Page Classification
AUTHORS:
Kathirvalavakumar Thangairulappan, Aruna Devi Kanagavel
KEYWORDS:
Web Page Classification, Term-Weighting Scheme, Feature Selection, Feature Extraction, Artificial Neural Network, Back Propagation
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.8 No.4,
September
27,
2016
ABSTRACT: Automatic web page classification has
become inevitable for web directories due to the multitude of web pages in the
World Wide Web. In this paper an improved Term Weighting technique is proposed
for automatic and effective classification of web pages. The web documents are
represented as set of features. The proposed method selects and extracts the
most prominent features reducing the high dimensionality problem of classifier.
The proper selection of features among the large set improves the performance
of the classifier. The proposed algorithm is implemented and tested on a
benchmarked dataset. The results show the better performance than most of the
existing term weighting techniques.