A Genetic Programming Approach to Data Clustering
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @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