The Web Classification Based on ROUGH-GA-BP

Long Zhen Duan; Zhi Xin Zou; Gui Fen Wang

doi:10.4028/www.scientific.net/AMR.328-330.1037

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 328-330The Web Classification Based on ROUGH-GA-BP

The Web Classification Based on ROUGH-GA-BP

Abstract:

The shortcomings of the BP algorithm are analyzed, and a text classification algorithm based on rough-GA-BP is constructed by combining the genetic algorithm with the rough sets theory. This algorithm reduces the data of the text input vector by the data reduction method based on rough sets theory, and presenting a genetic algorithm approach for feature selection. Experimental results indicate this method is more effective than traditional methods.

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Periodical:

Advanced Materials Research (Volumes 328-330)

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1037-1040

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.328-330.1037

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Online since:

September 2011

Authors:

Long Zhen Duan, Zhi Xin Zou, Gui Fen Wang

Keywords:

Data Reduction, ROUGH-GA-BP, Text Classification Algorithm

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References

[1] X.H. Lu and Y. Hu: Journal of Luoyang Technology College, Vol. 17 (2007) No. 6, p.8. (In Chinese).

Google Scholar

[2] X.C. Zheng, Z.D. Lin and K. Deng: Microcomputer Information, Vol. 25 (2009) No. 93, p.180. (In Chinese).

Google Scholar

[3] S. Fabrizio: ACM Computing Surveys, Vol. 34 (2002) No. 1, p.147.

Google Scholar

[4] Y.D. Kan, M.S. Ni and G.Q. Liu: Computer Application and Software, Vol. 26 (2009) No. 8, p.153. (In Chinese).

Google Scholar

[5] Q.H. Li and M.F. Zhang: Microcomputer Information, Vol. 22 (2006) No. 4, p.93. (In Chinese).

Google Scholar

[6] Z. Pawlak: International Journal of Computer and Information Science, Vol. 11 (1982) No. 5, p.341.

Google Scholar

[7] R.R. Jiang: Microcomputer Information, Vol. 23 (2007) No. 11-1, p.235. (In Chinese).

Google Scholar

[8] R.J. Bai and X.Y. Wang: Journal of Shandong University (Natural Science), Vol. 41 (2006) No. 3, p.70. (In Chinese).

Google Scholar

[9] F. Liu and B.X. Liu: Software Guide, Vol. 8 (2009) No. 9, p.66. (In Chinese).

Google Scholar

[10] R. Saian, K. Ruhana and K. Mahamud: 2nd International Conference on Computer and Network Technology (Bangkok, Thailand, April 23-25, 2010). Vol. 13, p.115.

Google Scholar

[11] C. Badue, F. Pedroni and A.F. De Souza: 10th Brazilian Symposium on Neural Networks (Salvador, Bahia, Brazil, Oct 26-30, 2008). Vol. 29, p.105.

Google Scholar