首页> 外文会议>International conference on future data and security engineering >Mining Incrementally Closed Itemsets over Data Stream with the Technique of Batch-Update
【24h】

Mining Incrementally Closed Itemsets over Data Stream with the Technique of Batch-Update

机译:使用批处理更新技术在数据流上增量关闭项目集的挖掘

获取原文

摘要

Currently incremental mining techniques can be divided into two groups: direct-update technique and batch-update technique. Mining closed item sets is one of the core tasks of data mining. In addition, advances in hardware technology and information technology have created huge data streams in recent years. Therefore, mining incrementally closed item sets over data streams with the batch-update technique is necessary. Incremental algorithms are always associated with an intermediate structure such as tree, lattice, table... In the previous study, the author proposed an intermediate structure which is a linear list called constructive set. In this paper, an incremental mining algorithm based on the constructive with the batch-update technique is proposed in order to mine data streams.
机译:当前,增量挖掘技术可以分为两类:直接更新技术和批量更新技术。挖掘封闭项目集是数据挖掘的核心任务之一。另外,近年来,硬件技术和信息技术的发展创造了巨大的数据流。因此,有必要使用批处理更新技术在数据流上挖掘增量式封闭项目集。增量算法总是与诸如树,格,表等中间结构相关联。在先前的研究中,作者提出了一种中间结构,该结构是称为构造集的线性列表。本文提出了一种基于构造与批处理更新的增量挖掘算法,以挖掘数据流。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号