Evolution of multiple tree structured patterns using soft clustering
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Yoshida:2010:ICCAE,
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author = "Kengo Yoshida and Tetsuhiro Miyahara and
Tetsuji Kuboyama",
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title = "Evolution of multiple tree structured patterns using
soft clustering",
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booktitle = "The 2nd International Conference on Computer and
Automation Engineering (ICCAE 2010)",
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year = "2010",
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month = "26-28 " # feb,
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volume = "5",
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pages = "749--753",
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address = "Singapore",
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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.",
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keywords = "genetic algorithms, genetic programming, multiple tag
tree patterns, multiple tree structured patterns, soft
clustering, tree structured data, pattern clustering,
trees (mathematics)",
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DOI = "doi:10.1109/ICCAE.2010.5451349",
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notes = "Also known as \cite{5451349}",
- }
Genetic Programming entries for
Kengo Yoshida
Tetsuhiro Miyahara
Tetsuji Kuboyama
Citations