Multiple Instance Learning with Genetic Programming for Web Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{conf/iwann/ZafraVHR07,

• author = "Amelia Zafra and Sebastian Ventura and Enrique Herrera-Viedma and Cristobal Romero",
• title = "Multiple Instance Learning with Genetic Programming for Web Mining",
• booktitle = "Proceedings of the 9th International Work-Conference on Artificial Neural Networks, IWANN 2007",
• year = "2007",
• editor = "Francisco Sandoval Hern{\'a}ndez and Alberto Prieto and Joan Cabestany and Manuel Gra{\~n}a",
• volume = "4507",
• series = "Lecture Notes in Computer Science",
• pages = "919--927",
• address = "San Sebasti{\'a}n, Spain",
• month = jun # " 20-22",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-73006-4",
• DOI = "doi:10.1007/978-3-540-73007-1_111",
• size = "9 pages",
• abstract = "The aim of this paper is to present a new tool of multiple instance learning which is designed using a grammar based genetic programming (GGP) algorithm. We study its application in Web Mining framework to identify web pages interesting for the users. This new tool called GGP-MI algorithm is evaluated and compared with other available algorithms which extend a well-known neighborhood based algorithm (k-nearest neighbour algorithm) to multiple instance learning. Computational experiments show that, the GGP-MI algorithm obtains competitive results, solves problems of other algorithms, such as sparsity and scalability and adds comprehensibility and clarity in the knowledge discovery process.",
• notes = "Computational and Ambient Intelligence",
• bibdate = "2007-09-29",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iwann/iwann2007.html#ZafraVHR07",

}

Genetic Programming entries for Amelia Zafra Gomez Sebastian Ventura Enrique Herrera Viedma Cristobal Romero Morales

Citations