Journal of Guangxi Normal University(Natural Science Edition) ›› 2010, Vol. 28 ›› Issue (3): 140-143.

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An Improved Short Text Classification Algorithm Based on Bayesian Network

GUO Si-hui, FAN Xing-hua   

  1. Institute of Computer Science and Technology,Chongqing University of Posts and Telecommunications, Chongqing 400065,China
  • Received:2010-05-31 Online:2010-09-20 Published:2023-02-06

Abstract: Due to the fact that inadequate features of short text makes unsatisfactory classification,an improved algorithm fortext classification based on Bayesian network is presented.The improvement liesin the steps of Bayesian networkstructure learning phase for finding parent node.The algorithm takes into account the connection strength of the factors,thus,a decrease of interference errors between two nodes that are unrelated to the father and son nodes is achieved.It enables each node to find more accurate father node,and improves the classification accuracy of text.

Key words: Bayesian network, connection strength, short text classification

CLC Number: 

  • TP391.4
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