Evolution of multiple tree structured patterns using soft clustering

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Yoshida:2010:ICCAE,

• author = "Kengo Yoshida and Tetsuhiro Miyahara and Tetsuji Kuboyama",
• title = "Evolution of multiple tree structured patterns using soft clustering",
• booktitle = "The 2nd International Conference on Computer and Automation Engineering (ICCAE 2010)",
• year = "2010",
• month = "26-28 " # feb,
• volume = "5",
• pages = "749--753",
• address = "Singapore",
• abstract = "We propose a new genetic programming (GP) approach to extracting multiple tree structured patterns from tree structured data using soft clustering. We use a set of multiple tree structured patterns, called tag tree patterns, as a combined pattern. A structured variable in a tag tree pattern can be substituted by an arbitrary tree. A set of multiple tag tree patterns matches a tree, if at least one of the set of patterns matches the tree. Using soft clustering is appropriate because one tree structured data is allowed to match multiple tag tree patterns. By soft clustering of positive data and by running GP subprocesses on each cluster with negative data, we make a combined pattern which consists of best individuals in GP subprocesses. Experiments on some glycan data show that our method has a support of about 0.8, while the previous method for evolving single patterns has a support of about 0.5.",
• keywords = "genetic algorithms, genetic programming, multiple tag tree patterns, multiple tree structured patterns, soft clustering, tree structured data, pattern clustering, trees (mathematics)",
• DOI = "doi:10.1109/ICCAE.2010.5451349",
• notes = "Also known as \cite{5451349}",

}

Genetic Programming entries for Kengo Yoshida Tetsuhiro Miyahara Tetsuji Kuboyama

Citations