J4 ›› 2012, Vol. 30 ›› Issue (5): 540-.

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Semi-Structured Data Model Extraction Based on Frequent Patterns

LI Ying1, ZHANG Xiao-xian2, SUN Jia-hui3   

  1. 1. College of Computer Science, Jilin Normal University, Siping 136000, China;2. College of Software, Changchun Institute of Technology, Changchun 130012, China;3. Department of Basic, Aviation University of Air Force, Changchun 130022, China
  • Online:2012-09-28 Published:2012-11-01

Abstract:

In order to overcome the complex characteristics of semi-structured data storage, we propose a semi-structured storage model based on dynamic tree. We extract mode by introducing the mode into the Apriori algorithm, and setting the minimum support threshold filter unnecessary information to output the longest frequent path collection. Experimental results show that this algorithm deal effectively with the branch and loop part at the same time, and also it can avoid infinite loop.

Key words: semi-structured data, data mining, frequent patterns mining, extracting schema

CLC Number: 

  • TP31