吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (3): 903-908.doi: 10.13229/j.cnki.jdxbgxb20170114

• Orginal Article • Previous Articles     Next Articles

Improved DNALA algorithm based on spectral clustering matrix

DENG Jian-xun1,2, XIONG Zhong-yang1, DENG Xin3   

  1. 1.College of Computer Science,Chongqing University,Chongqing 400044,China;
    2.School of Software,Chongqing College of Electronic Engineering,Chongqing 401331,China;
    3.School of Computer Science and Technology, Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • Received:2017-02-16 Online:2018-05-20 Published:2018-05-20

Abstract: Traditional DNALA algorithm has the shortcomings of low efficiency in terms of running time and unsatisfactory accuracy of the data mining results. To overcome these shortcomings, an improved DNALA algorithm is proposed based spectral clustering matrix, called DNALA-I, which can improve the time efficiency and accuracy of the results. The calculation of the distance matrix by multi sequence ratios in the traditional DNALA algorithm is improved by calculation of the spectral clustering distance matrix in the DNALA-I algorithm. Experiment results show that, compared with the traditional DNALA algorithm, the proposed DNALA-I algorithm can effectively reduce the time for sequence alignment meanwhile remain the data mining accuracy.

Key words: computer application, privacy protection, data mining, DNALA algorithm, spectrum clustering matrix

CLC Number: 

  • TP391
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