Title :
Text Classification Based on Ant Colony Optimization
Author :
Jiao, Lijuan ; Feng, Liping
Author_Institution :
Dept. of Comput. Sci., Xinzhou Teachers Univ., Xinzhou, China
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;
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
DOI :
10.1109/ICIC.2010.242
