DocumentCode :
2020796
Title :
Research of Text Classification Technology based on Genetic Annealing Algorithm
Author :
Zhen-fang, Zhu ; Pei-yu, Liu ; Ran, Lu
Author_Institution :
Shandong Normal Univ., Jinan
Volume :
1
fYear :
2008
fDate :
17-18 Oct. 2008
Firstpage :
265
Lastpage :
269
Abstract :
Text classification has received extensive attention in recent years, which is an important means of data mining. This paper analyzed basic theory and general structure of text classification, given a text classification method based on improved genetic algorithms, introduced simulated annealing mechanism of genetic algorithm to solve the precocious easy, local optimum, and so on, using the Roocchio feedback model to achieve feedback and self-learning of text classification. Experiment, we used this method to achieve a text classification system and the traditional KNN classification method were compared, results showed that the training methods for text classification has good accuracy and recall rate.
Keywords :
feedback; genetic algorithms; simulated annealing; text analysis; Roocchio feedback model; genetic annealing algorithm; simulated annealing mechanism; text classification technology; Algorithm design and analysis; Annealing; Classification algorithms; Computational intelligence; Data mining; Feedback; Genetic algorithms; Support vector machine classification; Support vector machines; Text categorization; GA; Text classification; feedback; simulated annealing mechanism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3311-7
Type :
conf
DOI :
10.1109/ISCID.2008.83
Filename :
4725605
Link To Document :
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