文章基本信息

标题：Recent Frequent Item Mining Algorithm in a Data Stream Based on Flexible Counter Windows
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作者：Guo, Yanyang ; Wang, Gang ; Hou, Fengmei 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2014
卷号：9
期号：1
页码：258-263
DOI：10.4304/jsw.9.1.258-263
语种：English
出版社：Academy Publisher
摘要：In the paper the author introduces FCW_MRFI, which is a streaming data frequent item mining algorithm based on variable window. The FCW_MRFI algorithm can mine frequent item in any window of recent streaming data, whose given length is L. Meanwhile, it divides recent streaming data into several windows of variable length according to m, which is the number of the counter array. This algorithm can achieve smaller query error in recent windows, and can minimize the maximum query error in the whole recent streaming data.
关键词：streaming data;counter array;data mining;most recent frequent item