DocumentCode
3073790
Title
Text Classification Based on Ant Colony Optimization
Author
Jiao, Lijuan ; Feng, Liping
Author_Institution
Dept. of Comput. Sci., Xinzhou Teachers Univ., Xinzhou, China
Volume
3
fYear
2010
fDate
4-6 June 2010
Firstpage
229
Lastpage
232
Abstract
A new text classification algorithm which is based on Ant Colony Algorithm is proposed in this paper. It makes use of the advantage in solving discrete problems by ACO and discreteness of text documents´ features. Texts are classified by crawling of class population ants which have class information with them to find an optimal path matching it during iteration in the algorithm. It can get a satisfactory classification by the experiment.
Keywords
optimisation; pattern classification; text analysis; ant colony optimization; optimal path matching; text classification algorithm; text documents features; Ant colony optimization; Biological system modeling; Biomedical signal processing; Classification algorithms; Clustering algorithms; Computer science; Electronic mail; Roads; Signal processing algorithms; Text categorization; Colony Optimization; Feature; Text classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Computing (ICIC), 2010 Third International Conference on
Conference_Location
Wuxi, Jiang Su
Print_ISBN
978-1-4244-7081-5
Electronic_ISBN
978-1-4244-7082-2
Type
conf
DOI
10.1109/ICIC.2010.242
Filename
5513964
Link To Document