吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (4): 1054-1058.

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IL-AdaBoost algorithm for XML document classification

DONG Yuan-fang1,2, LI Xiong-fei1, LI Jun1,3,LI Wei1   

  1. 1.Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education, Jilin University, Changchun 130012, China|2.School of Economics and Management, Changchun University of Science and Technology, Changchun 130022, China|3.Department of Mathematics, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2010-05-17 Online:2011-07-01 Published:2011-07-01

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Abstract:

An improved AdaBoost algorithm, IL-AdaBoost, for XML document classification is proposed. IL-AdaBoost uses frequent change of substructure with XML as the feature to build the decision stumps, then uses the decision stumps as weak classifiers, and improves AdaBoost algorithm. IL-AdaBoost is used to simulate new generation of XML documents through Poisson process, which reflects the characteristics of increase in XML documents with time, and updates the distribution of the sample to achieve incremental learning. IL-AdaBoost reduces the differences of basic classifier by sampling, and improves ensemble learning.

Key words: artificial intelligence, AdaBoost, XML classification, feature space, incremental learning

CLC Number: 

  • TP181
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