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A Comparative Study on the Effect of used Crossover Operator on Performance of GA as a Web Page Classifier

by Neda Sabouri, Hamid Haj Seyyed Javadi, Toktam Zhiani Asoudeh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 71 - Number 23
Year of Publication: 2013
Authors: Neda Sabouri, Hamid Haj Seyyed Javadi, Toktam Zhiani Asoudeh
10.5120/12629-9443

Neda Sabouri, Hamid Haj Seyyed Javadi, Toktam Zhiani Asoudeh . A Comparative Study on the Effect of used Crossover Operator on Performance of GA as a Web Page Classifier. International Journal of Computer Applications. 71, 23 ( June 2013), 32-37. DOI=10.5120/12629-9443

@article{ 10.5120/12629-9443,
author = { Neda Sabouri, Hamid Haj Seyyed Javadi, Toktam Zhiani Asoudeh },
title = { A Comparative Study on the Effect of used Crossover Operator on Performance of GA as a Web Page Classifier },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 71 },
number = { 23 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume71/number23/12629-9443/ },
doi = { 10.5120/12629-9443 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:36:28.678297+05:30
%A Neda Sabouri
%A Hamid Haj Seyyed Javadi
%A Toktam Zhiani Asoudeh
%T A Comparative Study on the Effect of used Crossover Operator on Performance of GA as a Web Page Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 71
%N 23
%P 32-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

By incredible and uncontrollable growth in amount of web pages on the World Wide Web, providing an infrastructure due to searching among them leads to appearance of topic specific crawling of the web. Process of focused crawlers is base on an automatic web page classification mechanism of belonging or not belonging the page to a particular topic. The Genetic algorithm (GA) is a common optimization and search technique, used as classifier of web pages. Crossover operation as one of the GA operators, by producing 2 children out of parents of past generation and determination of next generation through combining produced child, plays important roles in performance of this algorithm. Up to now many different crossover operators such as single-point, two-point and ring are presented. In this paper, we compare the effect of mentioned crossover operators on performance of GA algorithm as a web page classifier.

References
  1. Holland, J. 1975. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence", Cambridge, MA: MIT Press (1992).
  2. Ribeiro, A. , Fresno, V. , Garcia-alegre, M. , Guinea, D. and Carlos, J. 2003. Web page classification, A soft computing approach, Lecture Notes in Artificial Intelligence, 2663, pp. 103-112.
  3. Pietramala, A. , Policicchio, V. , Rullo, P. and Sidhu, I. 2008. A Genetic Algorithm for Text Classification Rule Induction, Lecture Notes in Artificial Intelligence, 5212, pp. 188-203.
  4. Özel, S. 2010. A Web Page Classification System Based on a Genetic Algorithm Using Tagged-Terms as Features", Expert Systems with Applications.
  5. Reeves, C. and Rowe, J. 2003. Genetic Algorithms Principles and Perspectives, Kluwer Academic Publishers. Dordrecht.
  6. Kellegoz, T. , Toklu, B. and Wilson, J. 2008. Comparing efficiencies of genetic crossover operators for one machine total weighted tardiness problem, Applied Mathematics and Computation , Vol 199, pp. 590–598.
  7. Kaya, M. 2011. The effects of two new crossover operators on genetic algorithm performance, Applied Soft Computing, 11, pp. 881–890.
  8. Kaya, Y. , Uyar, M. and Tekin, R. 2011. A Novel Crossover Operator for Genetic Algorithms: Ring Crossover, Computing Research Repository Journal, Vol . abs/1105. 0.
  9. Chinnasri, W. 2012. Performance comparison of Genetic Algorithm's crossover operators on University Course Timetabling Problem , Computing Technology and Information Management, vol. 2, pp. 781-786.
  10. Craven, M. , Dipasquo, D. , Freitag, D. , Mccallum, A. , Mitchell, T. , Nigam, K. and Slattery, S. 1998. Learning to Extract Symbolic Knowledge from the World Wide Web, The 15th national conference on artificial intelligence, pp. 509-516.
  11. Kim, S. and Zhang, B. 2003. Genetic mining of html structures for effective web document retrieval, Applied Intelligence, 18, pp. 243-256.
  12. Trotman, A. 2005. Choosing document structure weights, Information Processing and management, 41(2), pp. 243-264.
  13. Porter, M. 1980. An algorithm for suffix stripping", Program, 14(3), pp. 130-137.
  14. Salton, Wong and Yang. 1975. A vector space model for automatic indexing, Communications of the ACM ,18(11),pp. 613-620.
  15. Kamber, M. and Han, J. 2008. Data mining: Concepts and Techniques (2nd ed), San Francisco, Morgan Kaufman publisher, ISBN 1-55860-901-6.
  16. Yang, Y. and Pedersen, J. O. 1997. A comparative study on feature selection in text categorization, the Fourteenth International Conference on Machine Learning (ICML-97), 412–420.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic algorithm web mining Crossover Operator Classification

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