Evolution of Multiple Tree Structured Patterns from Tree-Structured Data Using Clustering

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{DBLP:conf/ausai/NagamineMKUT08,
  author =       "Masatoshi Nagamine and Tetsuhiro Miyahara and 
                 Tetsuji Kuboyama and Hiroaki Ueda and Kenichi Takahashi",
  title =        "Evolution of Multiple Tree Structured Patterns from
                 Tree-Structured Data Using Clustering",
  editor =       "Wayne Wobcke and Mengjie Zhang",
  booktitle =    "AI 2008: 21st Australasian Joint Conference on
                 Artificial Intelligence",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "5360",
  year =         "2008",
  pages =        "500--511",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  address =      "Auckland, New Zealand",
  month =        dec # " 1-5",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-89377-6",
  DOI =          "doi:10.1007/978-3-540-89378-3_51",
  abstract =     "We propose a new genetic programming approach to
                 extraction of multiple tree structured patterns from
                 tree-structured data using clustering. As a combined
                 pattern we use a set of tree structured patterns,
                 called tag tree patterns. A structured variable in a
                 tag tree pattern can be substituted by an arbitrary
                 tree. A set of tag tree patterns matches a tree, if at
                 least one of the set of patterns matches the tree. By
                 clustering positive data and running GP subprocesses on
                 each cluster with negative data, we make a combined
                 pattern which consists of best individuals in GP
                 subprocesses. The experiments on some glycan data show
                 that our proposed method has a higher support of about
                 0.8 while the previous method for evolving single
                 patterns has a lower support of about 0.5.",
}

Genetic Programming entries for Masatoshi Nagamine Tetsuhiro Miyahara Tetsuji Kuboyama Hiroaki Ueda Ken-ichi Takahashi

Citations