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文章基本信息

  • 标题:An Effective Algorithm for Mining and Grouping Online Transactions in Online Systems
  • 本地全文:下载
  • 作者:Narasimham Parimi ; Mirza Mohsin Raza ; Prof. S.V.Achutha Rao
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2013
  • 卷号:4
  • 期号:9-1
  • 出版社:Seventh Sense Research Group
  • 摘要:Online transaction data between online visitors and online functionalities usually convey users’ taskoriented behavior models. Grouping online transactions might be captured knowledge which provides information, in return, creating user accounts, which may be associated with different navigational models. Some future online applications like, online recommendations or online personalized applications, the previous related works is most important to make online users get their preferred information accurately. We demonstrated usability and scalability of the proposed approach through performing experiments on two real world data sets. The practical results have proved the method’s effectiveness in comparison with some previous studies.
  • 关键词:clustering; recommendations; scalability
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