Genetic Programming Approach to Hierarchical Production Rule Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Al-Maqaleh:2007:isi,

• author = "Basheer M. Al-Maqaleh and Kamal K. Bharadwaj",
• title = "Genetic Programming Approach to Hierarchical Production Rule Discovery",
• journal = "International Science Index",
• year = "2007",
• volume = "1",
• number = "11",
• pages = "531--534",
• keywords = "genetic algorithms, genetic programming, hierarchy, knowledge discovery in database, subsumption matrix. k",
• publisher = "World Academy of Science, Engineering and Technology",
• index = "International Science Index 11, 2007",
• bibsource = "http://waset.org/Publications",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.308.1481",
• ISSN = "1307-6892",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.1481",
• URL = "http://waset.org/publications/10022",
• size = "4 pages",
• 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