文章基本信息

标题：Mining Closed Regular Patterns in Data Streams
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作者：M.Sreedevi ; L.S.S.Reddy
期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2013
卷号：5
期号：1
页码：171
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Mining regular patterns in data streams is an emerging research area and also a challenging problem inpresent days because in Data streams new data comes continuously with varying rates. Closed item setmining gained lot of implication in data mining research from conventional mining methods. So in thispaper we propose a narrative approach called CRPDS (Closed Regular Patterns in Data Streams) withvertical data format using sliding window model. To our knowledge no method has been proposed to mineclosed regular patterns in data streams. As the stream flows our CRPDS-method mines closed regularitemsets based on regularity threshold and user given support count. The experimental results show thatthe proposed method is efficient and scalable in terms of memory and time.
关键词：Data Streams; Regular patterns; closed regular patterns; transaction sliding window.