Fitness Function Obtained from a Genetic Programming Approach for Web Document Clustering Using Evolutionary Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.7929

@InProceedings{conf/iberamia/CobosMMLH12,

• author = "Carlos Cobos and Leydy Munoz and Martha Mendoza and Elizabeth {Leon Guzman} and Enrique Herrera-Viedma",
• title = "Fitness Function Obtained from a Genetic Programming Approach for Web Document Clustering Using Evolutionary Algorithms",
• booktitle = "Proceedings of the 13th Ibero-American Conference on {AI}, {IBERAMIA} 2012",
• year = "2012",
• editor = "Juan Pavon and Nestor D. Duque-Mendez and Ruben Fuentes-Fernandez",
• volume = "7637",
• series = "Lecture Notes in Computer Science",
• pages = "179--188",
• address = "Cartagena de Indias, Colombia",
• month = nov # " 13-16",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, web document clustering, clustering of web results, Bayesian information criteria",
• isbn13 = "978-3-642-34653-8",
• URL = "http://dx.doi.org/10.1007/978-3-642-34654-5",
• DOI = "doi:10.1007/978-3-642-34654-5_19",
• bibdate = "2012-11-17",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iberamia/iberamia2012.html#CobosMMLH12",
• size = "10 pages",
• abstract = "Web document clustering (WDC) is an alternative means of searching the web and has become a rewarding research area. Algorithms for WDC still present some problems, in particular: inconsistencies in the content and description of clusters. The use of evolutionary algorithms is one approach for improving results. It uses standard index to evaluate the quality (as a fitness function) of different solutions of clustering. Indexes such as Bayesian Information Criteria (BIC), Davies-Bouldin, and others show good performance, but with much room for improvement. In this paper, a modified BIC fitness function for WDC based on evolutionary algorithms is presented. This function was discovered using a genetic program (from a reverse engineering view). Experiments on datasets based on DMOZ show promising results.",
• notes = "Advances in Artificial Intelligence",

}

Genetic Programming entries for Carlos Alberto Cobos Lozada Leydy Carolina Munoz Martha Eliana Mendoza Becerra Elizabeth Leon Guzman Enrique Herrera Viedma

Citations