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

机译:使用Batch-Update技术挖掘逐渐关闭的项目集通过数据流进行数据流

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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:目前增量挖掘技术可分为两组: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。此外,近年来,硬件技术和信息技术的进步创造了巨大的数据流。因此,需要逐步封闭的项目在具有批量更新技术的数据流上设置。增量算法始终与中间结构相关联,例如树,格子,表......在先前的研究中,作者提出了一种称为构造集的线性列表的中间结构。本文提出了一种基于与批量更新技术的建设性的增量挖掘算法,以达到数据流。

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