Research on Classification of Privacy Protection Based on Improved Particle Swarm Optimization Algorithm

Yu Chen; Yuan Xin Tang; Zhou Zhou

doi:10.4028/www.scientific.net/AMM.496-500.1861

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 496-500Research on Classification of Privacy Protection...

Research on Classification of Privacy Protection Based on Improved Particle Swarm Optimization Algorithm

Abstract:

In this paper, through the analysis of the characteristics of particle swarm optimization algorithm, combined with the specific circumstances of Bayesian network structure learning, proposed to based on improved particle swarm algorithm.The algorithm uses the BIC measure function as a standard Bayesian network, while preserving the optimal particle case, the possibility of a mutation operation is added to decrease the algorithm into a local optimum. Through a typical Asia network, show that the algorithm is feasible, and other related algorithm is better than the experiment, the effectiveness of the algorithm. In this paper, the algorithm is verified from two aspects of theory and experiments, the results show that the algorithm is feasible.

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Periodical:

Applied Mechanics and Materials (Volumes 496-500)

Pages:

1861-1864

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.496-500.1861

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Cite this paper

Online since:

January 2014

Authors:

Yu Chen, Yuan Xin Tang*, Zhou Zhou

Keywords:

Bayesian Network (BN), Data Mining (DM), Particle Swarm Optimization Algorithm, Privacy Protection

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* - Corresponding Author

References

[1] Yang Weijia. Protection of privacy information in data mining. Journal of Shanghai Jiao Tong University, (2008).

Google Scholar

[2] Zhou Zhichun. Privacy preserving data mining. Journal of HeFei University of Technology, (2008).

Google Scholar

[3] Li Meng. Randomization method of privacy preserving data mining. Computer engineering and science. 2009: 34-39.

Google Scholar

[4] Zhen Huang, Yongji Wang, Chuanjiang Yang, Chaozhong Wu. A new improved Quantum- behaved Particle Swarm Optimization model. Industrial Electronics and Applications, 2009: 1211-1218.

DOI: 10.1109/iciea.2009.5138456

Google Scholar

[5] Jiahai Wang, Yalan Zhou. Quantum-Behaved Particle Swarm Optimization with Generalized Local Search Operator for Global Optimization. Advanced Intelligent Computing Theories and Applications. 2007: 51-860.

DOI: 10.1007/978-3-540-74205-0_88

Google Scholar