A Genetic Programming Approach to Data Clustering

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

@InProceedings{conf/fgit/AhnOO11,

• author = "Chang Wook Ahn and Sanghoun Oh and Moonyoung Oh",
• title = "A Genetic Programming Approach to Data Clustering",
• booktitle = "Proceedings of the International Conference on Multimedia, Computer Graphics and Broadcasting (MulGraB 2011) Part {II}",
• editor = "Tai-Hoon Kim and Hojjat Adeli and William I. Grosky and Niki Pissinou and Timothy K. Shih and Edward J. Rothwell and Byeong Ho Kang and Seung-Jung Shin",
• year = "2011",
• volume = "263",
• series = "Communications in Computer and Information Science",
• pages = "123--132",
• address = "Jeju Island, Korea",
• month = dec # " 8-10",
• publisher = "Springer",
• note = "Held as Part of the Future Generation Information Technology Conference, {FGIT} 2011, in Conjunction with {GDC} 2011",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-27186-1",
• DOI = "doi:10.1007/978-3-642-27186-1_15",
• size = "10 pages",
• abstract = "This paper presents a genetic programming (GP) to data clustering. The aim is to accurately classify a set of input data into their genuine clusters. The idea lies in discovering a mathematical function on clustering regularities and then use the rule to make a correct decision on the entities of each cluster. To this end, GP is incorporated into the clustering procedures. Each individual is represented by a parsing tree on the program set. Fitness function evaluates the quality of clustering with regard to similarity criteria. Crossover exchanges sub-trees between parental candidates in a positionally independent fashion. Mutation introduces (in part) a new sub-tree with a low probability. The variation operators (i.e., crossover, mutation) offer an effective search capability to obtain the improved quality of solution and the enhanced speed of convergence. Experimental results demonstrate that the proposed approach outperforms a well-known reference.",
• affiliation = "School of Information & Communication Engineering, Sungkyunkwan University, Suwon, 440-746 Korea",
• bibdate = "2011-12-08",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/fgit/mulgrab2011-2.html#AhnOO11",

}

Genetic Programming entries for Chang Wook Ahn Sanghoun Oh Moonyoung Oh

Citations