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Positive and negative association rules based on sequential patterns

GUO Yue-bin,ZHAI Yan-fu,DONG Xiang-jun,YANG Yue-yue,LI Gang   

  1. Department of Computer Science and Technology, Shandong Institute of Light Industry, Jinan 250353, Shandong, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-10-24 Published:2006-10-24
  • Contact: GUO Yue-bin

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Abstract: Sequential patterns can predict company developing trends. The negative association rules can show the origin of bad factors, and the positive and negative association rules based on sequential patterns can offer more comprehensive information. The mining of the positive and negative association rules based on sequential patterns was given by combining the sequential patterns algorithm and the negative association rules algorithm and utilizing the correlation between item sets.

Key words: correlation , the negative association rules, the positive association rules, sequential pattern

CLC Number: 

  • TP311
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