Title :
Application of Cooperative Algorithm in Text Feature Acquiring
Author_Institution :
Sch. of Inf., Linyi Univ., Linyi, China
Abstract :
Text feature acquiring is the key to construct the classifier to classify the text, According to the problem that the text dimension of the original feature vector is reduced and accurate, put forward a text feature acquiring algorithm based on co evolution, the algorithm uses genetic algorithm optimization performance and co evolution can implement multiple population mutual evaluation and competition, effectively reduce the dimension of feature vector of the original text, but also improve the accuracy and robustness of feature value vector, the experiment proved the effectiveness of this method.
Keywords :
Internet; genetic algorithms; text analysis; Internet; cooperative algorithm application; feature value vector; genetic algorithm optimization; multiple population mutual evaluation; original feature vector; text dimension; text feature acquiring algorithm; Biological cells; Classification algorithms; Feature extraction; Genetic algorithms; Sociology; Statistics; Text categorization; Cooperative Evolution; Feature Abstract; Genetic Agorithm; Text Categorization;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.82