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Improved Term Weighting Technique for Automatic Web Page Classification
Department of Computer Science, V. H. N. S. N. College, Virudhunagar, India
Department of Computer Science (PG), Kristu Jayanti College, Bengaluru, India
- 1 Department of Computer Science, V. H. N. S. N. College, Virudhunagar, India
- 2 Department of Computer Science (PG), Kristu Jayanti College, Bengaluru, India
Journal of Intelligent Learning Systems and Applications·Volume 08 (2016)·Pages 63–76·Published 27 September 2016·DOI10.4236/jilsa.2016.84006
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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.
KeywordsWeb Page ClassificationTerm-Weighting SchemeFeature SelectionFeature ExtractionArtificial Neural NetworkBack Propagation
- Qi, X.G. and Davison, B.D. (2009) Web Page Classification: Features and Algorithms. ACM Computing Surveys, 41, 12:1-12:31.
- McCallum, A. and Nigam, K. (1998) A Comparison of Event Models for Naive Bayes Text Classification. Proceedings in Workshop on Learning for Text Categorization, AAAI’98, 41-48.
- Lewis, D.D., Schapire, R.E., Callan, J.P. and Papka, R. (1996) Training Algorithms for Linear Text Classifiers. Proceedings of 19th International Conference on Research and development in Information Retrieval, ACM, New York, 289-297. http://dx.doi.org/10.1145/243199.243277
- Yang, Y., Slattery, S. and Ghani, R. (2002) A Study of Approaches to Hypertext Categorization. Journal of Information Systems, 18, 2-3.
- Kamruzzaman, S.M. (2006) Web Page Categorization Using Artificial Neural Networks. Proceedings of the 4th Intl Conf. on Electrical Engg. & 2nd Annual Paper Meet, Bangladesh, January 2006, 26-28.
- Selamat, A. and Omatu, S. (2004) Web Page Feature Selection and Classification Using Neural Networks. Information Sciences, 158, 69-88. http://dx.doi.org/10.1016/j.ins.2003.03.003
- Selamat, A., Lee, Z.S., Maarof, M.A. and Shamsuddin, S.M. (2011) Improved Web Page Identification Method using Neural Networks. International Journal of Computational Intelligence and Applications, 10, 87-114. http://dx.doi.org/10.1142/S1469026811003008
- Sabbah, T., Selamat, A., Selamat, M.H., Ibrahim, R. and Fujita, H. (2016) Hybridized Term Weighting Method for Web Contents Classification using SVM. Neuro Computing, 173, 1908-1926. http://dx.doi.org/10.1016/j.neucom.2015.09.063
- Shanthi, S.G. and Thanamani, A.S. (2012)Enhanced Approach on Web Page Classification Using Machine Learning Technique. International Journal of Advanced Research in Computer Engineering & Technology, 1, 278-282.
- Alamelu Mangai, J., Santhosh Kumar, V. and Appavu Balamurugan, S. (2013) A Novel Approach for Effective Web Page Classification. International Journal of Data Mining Modelling and Management, 5, 233-245. http://dx.doi.org/10.1504/IJDMMM.2013.055860
- Dutta, R., Kundu, A. and Mukhopadhyay, D. (2011) Clustering-Based Web Page Prediction. International Journal of Knowledge and Web Intelligence, 2, 257-271. http://dx.doi.org/10.1504/IJKWI.2011.045163
- Luo, Q.M., Chen, E.H. and Xiong, H. (2011) A Semantic Term Weighting Scheme for Text Categorization. Expert Systems with Applications, 38, 12708-12716. http://dx.doi.org/10.1016/j.eswa.2011.04.058