Indexing Based Feature Selection by Applying Ant Colony Optimization Method for Improving Web Page Classification

In this information age many research work are carried out in web page classification to acquire the relevant and appropriate information. To be more specific, for enhancing the web page classification to obtain the optimized feature sets are chosen by utilizing the evolutionary algorithms. Normally, these algorithms are designed by the heuristic principles stimulated by natural evolution. After analyzing the significance of the various evolutionary algorithms deployed by several researchers in this domain so far, this work also intended to apply them to acquire the best solutions (enhanced features). In general, applying the evolutionary algorithms the fittest genes are generated and determined by the fitness function. Once the fittest genes are decided picking up the fittest individual genomes from a population for taking them to the next generations is the challenging task. In this article a novel approach is proposed to choose the best solutions.

[1]  Sonali Rangdale,et al.  Automatic Template Extraction from Heterogeneous Web Pages , 2014 .

[2]  Mengjie Zhang,et al.  Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach , 2013, IEEE Transactions on Cybernetics.

[3]  G. Galindo.  Del Prometeo griego al de la era-biós de la tecnociencia. Reflexiones bioéticas , 2017 .

[4]  Qingyu Zhang,et al.  Web Mining: a Survey of Current Research, Techniques, and Software , 2008, Int. J. Inf. Technol. Decis. Mak..

[5]  Sheng-Tang Wu,et al.  Pattern-Based Web Mining Using Data Mining Techniques , 2013 .

[6]  Kyuseok Shim,et al.  TEXT: Automatic Template Extraction from Heterogeneous Web Pages , 2011, IEEE Transactions on Knowledge and Data Engineering.

[7]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[8]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[10]  Yan Li,et al.  Research on Web mining-based intelligent search engine , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.

[11]  Tim Hendtlass,et al.  Particle Swarm Optimisation and high dimensional problem spaces , 2009, 2009 IEEE Congress on Evolutionary Computation.

[12]  P. Venkatesh,et al.  Multiobjective evolutionary computation algorithms for solving task scheduling problem on heterogeneous systems , 2010, Int. J. Knowl. Based Intell. Eng. Syst..