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