Title :
Optimization of text feature subsets based on GATS algorithm
Author :
Jiang, Pei-Pei ; Liu, Pei-Yu ; Zhu, Zhen-Fang ; Zhao, Li-Na
Author_Institution :
Dept. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
Abstract :
For feature subset optimization problems in text categorization, the GATS strategy which combines the genetic algorithm with taboo search algorithm is proposed in this paper to be applied to text categorization to realize the dimensionality reduction of the feature space. The experiments show that the application of this method to select the characteristics of the text can not only maintain the advantages of the GA and the TS algorithm themselves, but also improve the classification accuracy of the text.
Keywords :
combinatorial mathematics; genetic algorithms; mathematical operators; pattern classification; search problems; text analysis; GATS algorithm; dimensionality reduction; feature subset optimization problems; genetic algorithm with taboo search algorithm; text categorization; text feature subsets; Approximation algorithms; Data mining; Genetic algorithms; Guidelines; Information retrieval; Internet; Machine learning algorithms; Optimization methods; Space technology; Text categorization;
Conference_Titel :
IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-3928-7
Electronic_ISBN :
978-1-4244-3930-0
DOI :
10.1109/ITIME.2009.5236207
