Genetic Programming Approach to Hierarchical Production Rule Discovery
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Al-Maqaleh:2007:isi,
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author = "Basheer M. Al-Maqaleh and Kamal K. Bharadwaj",
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title = "Genetic Programming Approach to Hierarchical
Production Rule Discovery",
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journal = "International Science Index",
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year = "2007",
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volume = "1",
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number = "11",
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pages = "531--534",
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keywords = "genetic algorithms, genetic programming, hierarchy,
knowledge discovery in database, subsumption matrix.
k",
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publisher = "World Academy of Science, Engineering and Technology",
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index = "International Science Index 11, 2007",
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bibsource = "http://waset.org/Publications",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.308.1481",
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ISSN = "1307-6892",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.1481",
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URL = "http://waset.org/publications/10022",
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size = "4 pages",
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abstract = "Automated discovery of hierarchical structures in
large data sets has been an active research area in the
recent past. This paper focuses on the issue of mining
generalised rules with crisp hierarchical structure
using Genetic Programming (GP) approach to knowledge
discovery. The post-processing scheme presented in this
work uses flat rules as initial individuals of GP and
discovers hierarchical structure. Suitable genetic
operators are proposed for the suggested encoding.
Based on the Subsumption Matrix(SM), an appropriate
fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the
discovered hierarchy. Experimental results are
presented to demonstrate the performance of the
proposed algorithm.",
- }
Genetic Programming entries for
Basheer Mohamad Ahmad Al-Maqaleh
K K Bharadwaj
Citations