吉林大学学报(工学版) ›› 2000, Vol. ›› Issue (3): 47-50.

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Synthetic Data Generation on Association Rules

CHENG Xiao-qing1, YUAN Sen-miao2   

  1. 1. College of Sciences, Jilin University of Technology, Changchun 130025, China;
    2. College of Information Science & Engineering, Jilin University of Technology, Changchun 130025, China
  • Received:1999-12-24 Online:2000-07-25

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Abstract: This paper develops algorithms on synthetic data generation based on the mathematic model presented by IBM Almaden Center.Synthetic data generaion is the test foundation of association rule research.To verify that the new algorithm is advanced to the existings on performances and scalibility,the authors need to compare existing algorithms with new algorithms on various kinds of datasets different in size and potentially strong item size.The research makes it releasable and the result is relatively satisfactory.

Key words: data mining, association rules, synthetic data generation

CLC Number: 

  • TP311.131
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