• DocumentCode
    2533696
  • Title

    Dual-strategy Analysis Model Based on Clustering and Inter-transaction

  • Author

    Sun, Fan ; Ren, Yonggong ; Qi, Yanyan

  • Author_Institution
    Sch. of Comput. & Inf. Technol., Liaoning Normal Univ., Dalian, China
  • fYear
    2011
  • fDate
    21-23 Oct. 2011
  • Firstpage
    78
  • Lastpage
    81
  • Abstract
    Inter-transactional association rules mining is mainly used in mining significant association between different transaction, but the existing algorithm only focus on the efficiency or accuracy. In this study, we propose the inter-transactional association rules algorithm based on cluster and dual-strategy analysis model. The algorithm adopts dual-strategy interest model to judge the integrity of the inter-transactional association rules, make up for mining bugs, avoid the generation of false rules, improve the quality of the mining algorithm; And use of cluster analysis to remove a large number of redundant data in database, improve the efficiency of the algorithm. The experimental results show that the proposed algorithm improves accuracy and efficiency of inter-transactional association rules algorithm.
  • Keywords
    Markov processes; data mining; database management systems; pattern clustering; transaction processing; cluster analysis; clustering model; database; dual-strategy analysis model; dual-strategy interest model; inter-transactional association rules mining; Algorithm design and analysis; Analytical models; Association rules; Clustering algorithms; Databases; Markov processes; Prediction algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Applications Conference (WISA), 2011 Eighth
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4577-1812-0
  • Type

    conf

  • DOI
    10.1109/WISA.2011.22
  • Filename
    6093607