Computer Science ›› 2018, Vol. 45 ›› Issue (8): 203-207.doi: 10.11896/j.issn.1002-137X.2018.08.036

• Artificial Intelligence • Previous Articles     Next Articles

Improved Bayesian Algorithm Based Automatic Classification Method for Bibliography

YANG Xiao-hua1, GAO Hai-yun2   

  1. Zhicheng College,Fuzhou University,Fuzhou 350002,China1
    College of Physics and Information Engineering,Fuzhou University,Fuzhou 350016,China2
  • Received:2018-02-28 Online:2018-08-29 Published:2018-08-29

Abstract: Bayesian algorithm is widely used in the field of automatic classification for bibliography.This method usually adopts differential evolution method to estimate the probability items.However,the traditional differential evolution method is easy to fall into the local optimum when estimating the probability items,which reduces the accuracy of Bayesian classifcation.In view of this problem,this paper proposed an improved Bayesian algorithm based automatic classification method for bibliography.In this method,the optimal solution of probability items is estimated through multi-parent mutation and crossover operation,which improves the accuracy of Bayesian classification.In the process of automatic classification for bibliography,the ICTCLAS system is used to preprocess the text and then extract the term frequency-inverse document frequency features of texts.Then,the improved Bayesian estimation method is utilized to train and classify the features.Finally,the automatic classification for bibliography is achieved.Simulation results show that this method has a high classification accuracy.

Key words: Automatic classification for bibliography, Bayesian algorithm, Differential evolution, Feature extraction

CLC Number: 

  • TP391
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